packages feed

amazonka-ml 1.4.2 → 1.4.3

raw patch · 31 files changed

+566/−1227 lines, 31 filesdep ~amazonka-coredep ~amazonka-mldep ~amazonka-testPVP ok

version bump matches the API change (PVP)

Dependency ranges changed: amazonka-core, amazonka-ml, amazonka-test

API changes (from Hackage documentation)

Files

README.md view
@@ -8,7 +8,7 @@  ## Version -`1.4.2`+`1.4.3`   ## Description
amazonka-ml.cabal view
@@ -1,5 +1,5 @@ name:                  amazonka-ml-version:               1.4.2+version:               1.4.3 synopsis:              Amazon Machine Learning SDK. homepage:              https://github.com/brendanhay/amazonka bug-reports:           https://github.com/brendanhay/amazonka/issues@@ -74,7 +74,7 @@         , Network.AWS.MachineLearning.Types.Sum      build-depends:-          amazonka-core == 1.4.2.*+          amazonka-core == 1.4.3.*         , base          >= 4.7     && < 5  test-suite amazonka-ml-test@@ -94,9 +94,9 @@         , Test.AWS.MachineLearning.Internal      build-depends:-          amazonka-core == 1.4.2.*-        , amazonka-test == 1.4.2.*-        , amazonka-ml == 1.4.2.*+          amazonka-core == 1.4.3.*+        , amazonka-test == 1.4.3.*+        , amazonka-ml == 1.4.3.*         , base         , bytestring         , tasty
gen/Network/AWS/MachineLearning/CreateBatchPrediction.hs view
@@ -18,21 +18,11 @@ -- Stability   : auto-generated -- Portability : non-portable (GHC extensions) ----- Generates predictions for a group of observations. The observations to--- process exist in one or more data files referenced by a 'DataSource'.--- This operation creates a new 'BatchPrediction', and uses an 'MLModel'--- and the data files referenced by the 'DataSource' as information--- sources.+-- Generates predictions for a group of observations. The observations to process exist in one or more data files referenced by a 'DataSource'. This operation creates a new 'BatchPrediction', and uses an 'MLModel' and the data files referenced by the 'DataSource' as information sources. ----- 'CreateBatchPrediction' is an asynchronous operation. In response to--- 'CreateBatchPrediction', Amazon Machine Learning (Amazon ML) immediately--- returns and sets the 'BatchPrediction' status to 'PENDING'. After the--- 'BatchPrediction' completes, Amazon ML sets the status to 'COMPLETED'.+-- 'CreateBatchPrediction' is an asynchronous operation. In response to 'CreateBatchPrediction', Amazon Machine Learning (Amazon ML) immediately returns and sets the 'BatchPrediction' status to 'PENDING'. After the 'BatchPrediction' completes, Amazon ML sets the status to 'COMPLETED'. ----- You can poll for status updates by using the < GetBatchPrediction>--- operation and checking the 'Status' parameter of the result. After the--- 'COMPLETED' status appears, the results are available in the location--- specified by the 'OutputUri' parameter.+-- You can poll for status updates by using the < GetBatchPrediction> operation and checking the 'Status' parameter of the result. After the 'COMPLETED' status appears, the results are available in the location specified by the 'OutputUri' parameter. module Network.AWS.MachineLearning.CreateBatchPrediction     (     -- * Creating a Request@@ -97,8 +87,7 @@     , _cbpOutputURI = pOutputURI_     } --- | A user-supplied name or description of the 'BatchPrediction'.--- 'BatchPredictionName' can only use the UTF-8 character set.+-- | A user-supplied name or description of the 'BatchPrediction'. 'BatchPredictionName' can only use the UTF-8 character set. cbpBatchPredictionName :: Lens' CreateBatchPrediction (Maybe Text) cbpBatchPredictionName = lens _cbpBatchPredictionName (\ s a -> s{_cbpBatchPredictionName = a}); @@ -106,24 +95,17 @@ cbpBatchPredictionId :: Lens' CreateBatchPrediction Text cbpBatchPredictionId = lens _cbpBatchPredictionId (\ s a -> s{_cbpBatchPredictionId = a}); --- | The ID of the 'MLModel' that will generate predictions for the group of--- observations.+-- | The ID of the 'MLModel' that will generate predictions for the group of observations. cbpMLModelId :: Lens' CreateBatchPrediction Text cbpMLModelId = lens _cbpMLModelId (\ s a -> s{_cbpMLModelId = a}); --- | The ID of the 'DataSource' that points to the group of observations to--- predict.+-- | The ID of the 'DataSource' that points to the group of observations to predict. cbpBatchPredictionDataSourceId :: Lens' CreateBatchPrediction Text cbpBatchPredictionDataSourceId = lens _cbpBatchPredictionDataSourceId (\ s a -> s{_cbpBatchPredictionDataSourceId = a}); --- | The location of an Amazon Simple Storage Service (Amazon S3) bucket or--- directory to store the batch prediction results. The following--- substrings are not allowed in the s3 key portion of the \"outputURI\"--- field: \':\', \'\/\/\', \'\/.\/\', \'\/..\/\'.+-- | The location of an Amazon Simple Storage Service (Amazon S3) bucket or directory to store the batch prediction results. The following substrings are not allowed in the s3 key portion of the \"outputURI\" field: \':\', \'\/\/\', \'\/.\/\', \'\/..\/\'. ----- Amazon ML needs permissions to store and retrieve the logs on your--- behalf. For information about how to set permissions, see the--- <http://docs.aws.amazon.com/machine-learning/latest/dg Amazon Machine Learning Developer Guide>.+-- Amazon ML needs permissions to store and retrieve the logs on your behalf. For information about how to set permissions, see the <http://docs.aws.amazon.com/machine-learning/latest/dg Amazon Machine Learning Developer Guide>. cbpOutputURI :: Lens' CreateBatchPrediction Text cbpOutputURI = lens _cbpOutputURI (\ s a -> s{_cbpOutputURI = a}); @@ -170,12 +152,9 @@ instance ToQuery CreateBatchPrediction where         toQuery = const mempty --- | Represents the output of a < CreateBatchPrediction> operation, and is an--- acknowledgement that Amazon ML received the request.+-- | Represents the output of a < CreateBatchPrediction> operation, and is an acknowledgement that Amazon ML received the request. ----- The < CreateBatchPrediction> operation is asynchronous. You can poll for--- status updates by using the < GetBatchPrediction> operation and checking--- the 'Status' parameter of the result.+-- The < CreateBatchPrediction> operation is asynchronous. You can poll for status updates by using the < GetBatchPrediction> operation and checking the 'Status' parameter of the result. -- -- /See:/ 'createBatchPredictionResponse' smart constructor. data CreateBatchPredictionResponse = CreateBatchPredictionResponse'@@ -199,9 +178,7 @@     , _cbprsResponseStatus = pResponseStatus_     } --- | A user-supplied ID that uniquely identifies the 'BatchPrediction'. This--- value is identical to the value of the 'BatchPredictionId' in the--- request.+-- | A user-supplied ID that uniquely identifies the 'BatchPrediction'. This value is identical to the value of the 'BatchPredictionId' in the request. cbprsBatchPredictionId :: Lens' CreateBatchPredictionResponse (Maybe Text) cbprsBatchPredictionId = lens _cbprsBatchPredictionId (\ s a -> s{_cbprsBatchPredictionId = a});
gen/Network/AWS/MachineLearning/CreateDataSourceFromRDS.hs view
@@ -18,23 +18,11 @@ -- Stability   : auto-generated -- Portability : non-portable (GHC extensions) ----- Creates a 'DataSource' object from an--- <http://aws.amazon.com/rds/ Amazon Relational Database Service> (Amazon--- RDS). A 'DataSource' references data that can be used to perform--- < CreateMLModel>, < CreateEvaluation>, or < CreateBatchPrediction>--- operations.+-- Creates a 'DataSource' object from an <http://aws.amazon.com/rds/ Amazon Relational Database Service> (Amazon RDS). A 'DataSource' references data that can be used to perform < CreateMLModel>, < CreateEvaluation>, or < CreateBatchPrediction> operations. ----- 'CreateDataSourceFromRDS' is an asynchronous operation. In response to--- 'CreateDataSourceFromRDS', Amazon Machine Learning (Amazon ML)--- immediately returns and sets the 'DataSource' status to 'PENDING'. After--- the 'DataSource' is created and ready for use, Amazon ML sets the--- 'Status' parameter to 'COMPLETED'. 'DataSource' in 'COMPLETED' or--- 'PENDING' status can only be used to perform < CreateMLModel>,--- < CreateEvaluation>, or < CreateBatchPrediction> operations.+-- 'CreateDataSourceFromRDS' is an asynchronous operation. In response to 'CreateDataSourceFromRDS', Amazon Machine Learning (Amazon ML) immediately returns and sets the 'DataSource' status to 'PENDING'. After the 'DataSource' is created and ready for use, Amazon ML sets the 'Status' parameter to 'COMPLETED'. 'DataSource' in 'COMPLETED' or 'PENDING' status can only be used to perform < CreateMLModel>, < CreateEvaluation>, or < CreateBatchPrediction> operations. ----- If Amazon ML cannot accept the input source, it sets the 'Status'--- parameter to 'FAILED' and includes an error message in the 'Message'--- attribute of the < GetDataSource> operation response.+-- If Amazon ML cannot accept the input source, it sets the 'Status' parameter to 'FAILED' and includes an error message in the 'Message' attribute of the < GetDataSource> operation response. module Network.AWS.MachineLearning.CreateDataSourceFromRDS     (     -- * Creating a Request@@ -102,16 +90,11 @@ cdsfrdsDataSourceName :: Lens' CreateDataSourceFromRDS (Maybe Text) cdsfrdsDataSourceName = lens _cdsfrdsDataSourceName (\ s a -> s{_cdsfrdsDataSourceName = a}); --- | The compute statistics for a 'DataSource'. The statistics are generated--- from the observation data referenced by a 'DataSource'. Amazon ML uses--- the statistics internally during an 'MLModel' training. This parameter--- must be set to 'true' if the ''DataSource'' needs to be used for--- 'MLModel' training.+-- | The compute statistics for a 'DataSource'. The statistics are generated from the observation data referenced by a 'DataSource'. Amazon ML uses the statistics internally during an 'MLModel' training. This parameter must be set to 'true' if the ''DataSource'' needs to be used for 'MLModel' training. cdsfrdsComputeStatistics :: Lens' CreateDataSourceFromRDS (Maybe Bool) cdsfrdsComputeStatistics = lens _cdsfrdsComputeStatistics (\ s a -> s{_cdsfrdsComputeStatistics = a}); --- | A user-supplied ID that uniquely identifies the 'DataSource'. Typically,--- an Amazon Resource Number (ARN) becomes the ID for a 'DataSource'.+-- | A user-supplied ID that uniquely identifies the 'DataSource'. Typically, an Amazon Resource Number (ARN) becomes the ID for a 'DataSource'. cdsfrdsDataSourceId :: Lens' CreateDataSourceFromRDS Text cdsfrdsDataSourceId = lens _cdsfrdsDataSourceId (\ s a -> s{_cdsfrdsDataSourceId = a}); @@ -120,54 +103,31 @@ -- -   DatabaseInformation - -- --     -   'DatabaseName ' - Name of the Amazon RDS database.---     -   ' InstanceIdentifier ' - Unique identifier for the Amazon RDS---         database instance.--- -   DatabaseCredentials - AWS Identity and Access Management (IAM)---     credentials that are used to connect to the Amazon RDS database.+--     -   ' InstanceIdentifier ' - Unique identifier for the Amazon RDS database instance.+-- -   DatabaseCredentials - AWS Identity and Access Management (IAM) credentials that are used to connect to the Amazon RDS database. ----- -   ResourceRole - Role (DataPipelineDefaultResourceRole) assumed by an---     Amazon Elastic Compute Cloud (EC2) instance to carry out the copy---     task from Amazon RDS to Amazon S3. For more information, see---     <http://docs.aws.amazon.com/datapipeline/latest/DeveloperGuide/dp-iam-roles.html Role templates>---     for data pipelines.+-- -   ResourceRole - Role (DataPipelineDefaultResourceRole) assumed by an Amazon Elastic Compute Cloud (EC2) instance to carry out the copy task from Amazon RDS to Amazon S3. For more information, see <http://docs.aws.amazon.com/datapipeline/latest/DeveloperGuide/dp-iam-roles.html Role templates> for data pipelines. ----- -   ServiceRole - Role (DataPipelineDefaultRole) assumed by the AWS Data---     Pipeline service to monitor the progress of the copy task from---     Amazon RDS to Amazon Simple Storage Service (S3). For more---     information, see---     <http://docs.aws.amazon.com/datapipeline/latest/DeveloperGuide/dp-iam-roles.html Role templates>---     for data pipelines.+-- -   ServiceRole - Role (DataPipelineDefaultRole) assumed by the AWS Data Pipeline service to monitor the progress of the copy task from Amazon RDS to Amazon Simple Storage Service (S3). For more information, see <http://docs.aws.amazon.com/datapipeline/latest/DeveloperGuide/dp-iam-roles.html Role templates> for data pipelines. ----- -   SecurityInfo - Security information to use to access an Amazon RDS---     instance. You need to set up appropriate ingress rules for the---     security entity IDs provided to allow access to the Amazon RDS---     instance. Specify a ['SubnetId', 'SecurityGroupIds'] pair for a---     VPC-based Amazon RDS instance.+-- -   SecurityInfo - Security information to use to access an Amazon RDS instance. You need to set up appropriate ingress rules for the security entity IDs provided to allow access to the Amazon RDS instance. Specify a ['SubnetId', 'SecurityGroupIds'] pair for a VPC-based Amazon RDS instance. ----- -   SelectSqlQuery - Query that is used to retrieve the observation data---     for the 'Datasource'.+-- -   SelectSqlQuery - Query that is used to retrieve the observation data for the 'Datasource'. ----- -   S3StagingLocation - Amazon S3 location for staging RDS data. The---     data retrieved from Amazon RDS using 'SelectSqlQuery' is stored in---     this location.+-- -   S3StagingLocation - Amazon S3 location for staging RDS data. The data retrieved from Amazon RDS using 'SelectSqlQuery' is stored in this location. -- -- -   DataSchemaUri - Amazon S3 location of the 'DataSchema'. ----- -   DataSchema - A JSON string representing the schema. This is not---     required if 'DataSchemaUri' is specified.+-- -   DataSchema - A JSON string representing the schema. This is not required if 'DataSchemaUri' is specified. ----- -   DataRearrangement - A JSON string representing the splitting---     requirement of a 'Datasource'.+-- -   DataRearrangement - A JSON string representing the splitting requirement of a 'Datasource'. -----     Sample ----     ' \"{\\\"splitting\\\":{\\\"percentBegin\\\":10,\\\"percentEnd\\\":60}}\"'+--     Sample - ' \"{\\\"splitting\\\":{\\\"percentBegin\\\":10,\\\"percentEnd\\\":60}}\"' -- cdsfrdsRDSData :: Lens' CreateDataSourceFromRDS RDSDataSpec cdsfrdsRDSData = lens _cdsfrdsRDSData (\ s a -> s{_cdsfrdsRDSData = a}); --- | The role that Amazon ML assumes on behalf of the user to create and--- activate a data pipeline in the user’s account and copy data (using the--- 'SelectSqlQuery') query from Amazon RDS to Amazon S3.+-- | The role that Amazon ML assumes on behalf of the user to create and activate a data pipeline in the user’s account and copy data (using the 'SelectSqlQuery') query from Amazon RDS to Amazon S3. -- cdsfrdsRoleARN :: Lens' CreateDataSourceFromRDS Text cdsfrdsRoleARN = lens _cdsfrdsRoleARN (\ s a -> s{_cdsfrdsRoleARN = a});@@ -213,15 +173,9 @@ instance ToQuery CreateDataSourceFromRDS where         toQuery = const mempty --- | Represents the output of a < CreateDataSourceFromRDS> operation, and is--- an acknowledgement that Amazon ML received the request.+-- | Represents the output of a < CreateDataSourceFromRDS> operation, and is an acknowledgement that Amazon ML received the request. ----- The < CreateDataSourceFromRDS> operation is asynchronous. You can poll--- for updates by using the < GetBatchPrediction> operation and checking--- the 'Status' parameter. You can inspect the 'Message' when 'Status'--- shows up as 'FAILED'. You can also check the progress of the copy--- operation by going to the 'DataPipeline' console and looking up the--- pipeline using the pipelineId from the describe call.+-- The < CreateDataSourceFromRDS> operation is asynchronous. You can poll for updates by using the < GetBatchPrediction> operation and checking the 'Status' parameter. You can inspect the 'Message' when 'Status' shows up as 'FAILED'. You can also check the progress of the copy operation by going to the 'DataPipeline' console and looking up the pipeline using the pipelineId from the describe call. -- -- /See:/ 'createDataSourceFromRDSResponse' smart constructor. data CreateDataSourceFromRDSResponse = CreateDataSourceFromRDSResponse'@@ -245,8 +199,7 @@     , _cdsfrdsrsResponseStatus = pResponseStatus_     } --- | A user-supplied ID that uniquely identifies the datasource. This value--- should be identical to the value of the 'DataSourceID' in the request.+-- | A user-supplied ID that uniquely identifies the datasource. This value should be identical to the value of the 'DataSourceID' in the request. cdsfrdsrsDataSourceId :: Lens' CreateDataSourceFromRDSResponse (Maybe Text) cdsfrdsrsDataSourceId = lens _cdsfrdsrsDataSourceId (\ s a -> s{_cdsfrdsrsDataSourceId = a});
gen/Network/AWS/MachineLearning/CreateDataSourceFromRedshift.hs view
@@ -18,40 +18,15 @@ -- Stability   : auto-generated -- Portability : non-portable (GHC extensions) ----- Creates a 'DataSource' from--- <http://aws.amazon.com/redshift/ Amazon Redshift>. A 'DataSource'--- references data that can be used to perform either < CreateMLModel>,--- < CreateEvaluation> or < CreateBatchPrediction> operations.+-- Creates a 'DataSource' from <http://aws.amazon.com/redshift/ Amazon Redshift>. A 'DataSource' references data that can be used to perform either < CreateMLModel>, < CreateEvaluation> or < CreateBatchPrediction> operations. ----- 'CreateDataSourceFromRedshift' is an asynchronous operation. In response--- to 'CreateDataSourceFromRedshift', Amazon Machine Learning (Amazon ML)--- immediately returns and sets the 'DataSource' status to 'PENDING'. After--- the 'DataSource' is created and ready for use, Amazon ML sets the--- 'Status' parameter to 'COMPLETED'. 'DataSource' in 'COMPLETED' or--- 'PENDING' status can only be used to perform < CreateMLModel>,--- < CreateEvaluation>, or < CreateBatchPrediction> operations.+-- 'CreateDataSourceFromRedshift' is an asynchronous operation. In response to 'CreateDataSourceFromRedshift', Amazon Machine Learning (Amazon ML) immediately returns and sets the 'DataSource' status to 'PENDING'. After the 'DataSource' is created and ready for use, Amazon ML sets the 'Status' parameter to 'COMPLETED'. 'DataSource' in 'COMPLETED' or 'PENDING' status can only be used to perform < CreateMLModel>, < CreateEvaluation>, or < CreateBatchPrediction> operations. ----- If Amazon ML cannot accept the input source, it sets the 'Status'--- parameter to 'FAILED' and includes an error message in the 'Message'--- attribute of the < GetDataSource> operation response.+-- If Amazon ML cannot accept the input source, it sets the 'Status' parameter to 'FAILED' and includes an error message in the 'Message' attribute of the < GetDataSource> operation response. ----- The observations should exist in the database hosted on an Amazon--- Redshift cluster and should be specified by a 'SelectSqlQuery'. Amazon--- ML executes--- <http://docs.aws.amazon.com/redshift/latest/dg/t_Unloading_tables.html Unload>--- command in Amazon Redshift to transfer the result set of--- 'SelectSqlQuery' to 'S3StagingLocation.'+-- The observations should exist in the database hosted on an Amazon Redshift cluster and should be specified by a 'SelectSqlQuery'. Amazon ML executes <http://docs.aws.amazon.com/redshift/latest/dg/t_Unloading_tables.html Unload> command in Amazon Redshift to transfer the result set of 'SelectSqlQuery' to 'S3StagingLocation.' ----- After the 'DataSource' is created, it\'s ready for use in evaluations--- and batch predictions. If you plan to use the 'DataSource' to train an--- 'MLModel', the 'DataSource' requires another item -- a recipe. A recipe--- describes the observation variables that participate in training an--- 'MLModel'. A recipe describes how each input variable will be used in--- training. Will the variable be included or excluded from training? Will--- the variable be manipulated, for example, combined with another variable--- or split apart into word combinations? The recipe provides answers to--- these questions. For more information, see the Amazon Machine Learning--- Developer Guide.+-- After the 'DataSource' is created, it\'s ready for use in evaluations and batch predictions. If you plan to use the 'DataSource' to train an 'MLModel', the 'DataSource' requires another item -- a recipe. A recipe describes the observation variables that participate in training an 'MLModel'. A recipe describes how each input variable will be used in training. Will the variable be included or excluded from training? Will the variable be manipulated, for example, combined with another variable or split apart into word combinations? The recipe provides answers to these questions. For more information, see the Amazon Machine Learning Developer Guide. module Network.AWS.MachineLearning.CreateDataSourceFromRedshift     (     -- * Creating a Request@@ -119,11 +94,7 @@ cdsfrDataSourceName :: Lens' CreateDataSourceFromRedshift (Maybe Text) cdsfrDataSourceName = lens _cdsfrDataSourceName (\ s a -> s{_cdsfrDataSourceName = a}); --- | The compute statistics for a 'DataSource'. The statistics are generated--- from the observation data referenced by a 'DataSource'. Amazon ML uses--- the statistics internally during 'MLModel' training. This parameter must--- be set to 'true' if the ''DataSource'' needs to be used for 'MLModel'--- training+-- | The compute statistics for a 'DataSource'. The statistics are generated from the observation data referenced by a 'DataSource'. Amazon ML uses the statistics internally during 'MLModel' training. This parameter must be set to 'true' if the ''DataSource'' needs to be used for 'MLModel' training cdsfrComputeStatistics :: Lens' CreateDataSourceFromRedshift (Maybe Bool) cdsfrComputeStatistics = lens _cdsfrComputeStatistics (\ s a -> s{_cdsfrComputeStatistics = a}); @@ -136,42 +107,29 @@ -- -   DatabaseInformation - -- --     -   'DatabaseName ' - Name of the Amazon Redshift database.---     -   ' ClusterIdentifier ' - Unique ID for the Amazon Redshift---         cluster.--- -   DatabaseCredentials - AWS Identity abd Access Management (IAM)---     credentials that are used to connect to the Amazon Redshift---     database.+--     -   ' ClusterIdentifier ' - Unique ID for the Amazon Redshift cluster.+-- -   DatabaseCredentials - AWS Identity abd Access Management (IAM) credentials that are used to connect to the Amazon Redshift database. ----- -   SelectSqlQuery - Query that is used to retrieve the observation data---     for the 'Datasource'.+-- -   SelectSqlQuery - Query that is used to retrieve the observation data for the 'Datasource'. ----- -   S3StagingLocation - Amazon Simple Storage Service (Amazon S3)---     location for staging Amazon Redshift data. The data retrieved from---     Amazon Relational Database Service (Amazon RDS) using---     'SelectSqlQuery' is stored in this location.+-- -   S3StagingLocation - Amazon Simple Storage Service (Amazon S3) location for staging Amazon Redshift data. The data retrieved from Amazon Relational Database Service (Amazon RDS) using 'SelectSqlQuery' is stored in this location. -- -- -   DataSchemaUri - Amazon S3 location of the 'DataSchema'. ----- -   DataSchema - A JSON string representing the schema. This is not---     required if 'DataSchemaUri' is specified.+-- -   DataSchema - A JSON string representing the schema. This is not required if 'DataSchemaUri' is specified. ----- -   DataRearrangement - A JSON string representing the splitting---     requirement of a 'Datasource'.+-- -   DataRearrangement - A JSON string representing the splitting requirement of a 'Datasource'. -----     Sample ----     ' \"{\\\"splitting\\\":{\\\"percentBegin\\\":10,\\\"percentEnd\\\":60}}\"'+--     Sample - ' \"{\\\"splitting\\\":{\\\"percentBegin\\\":10,\\\"percentEnd\\\":60}}\"' -- cdsfrDataSpec :: Lens' CreateDataSourceFromRedshift RedshiftDataSpec cdsfrDataSpec = lens _cdsfrDataSpec (\ s a -> s{_cdsfrDataSpec = a}); --- | A fully specified role Amazon Resource Name (ARN). Amazon ML assumes the--- role on behalf of the user to create the following:+-- | A fully specified role Amazon Resource Name (ARN). Amazon ML assumes the role on behalf of the user to create the following: ----- -   A security group to allow Amazon ML to execute the 'SelectSqlQuery'---     query on an Amazon Redshift cluster+-- -   A security group to allow Amazon ML to execute the 'SelectSqlQuery' query on an Amazon Redshift cluster ----- -   An Amazon S3 bucket policy to grant Amazon ML read\/write---     permissions on the 'S3StagingLocation'+-- -   An Amazon S3 bucket policy to grant Amazon ML read\/write permissions on the 'S3StagingLocation' -- cdsfrRoleARN :: Lens' CreateDataSourceFromRedshift Text cdsfrRoleARN = lens _cdsfrRoleARN (\ s a -> s{_cdsfrRoleARN = a});@@ -217,12 +175,9 @@ instance ToQuery CreateDataSourceFromRedshift where         toQuery = const mempty --- | Represents the output of a < CreateDataSourceFromRedshift> operation,--- and is an acknowledgement that Amazon ML received the request.+-- | Represents the output of a < CreateDataSourceFromRedshift> operation, and is an acknowledgement that Amazon ML received the request. ----- The < CreateDataSourceFromRedshift> operation is asynchronous. You can--- poll for updates by using the < GetBatchPrediction> operation and--- checking the 'Status' parameter.+-- The < CreateDataSourceFromRedshift> operation is asynchronous. You can poll for updates by using the < GetBatchPrediction> operation and checking the 'Status' parameter. -- -- /See:/ 'createDataSourceFromRedshiftResponse' smart constructor. data CreateDataSourceFromRedshiftResponse = CreateDataSourceFromRedshiftResponse'@@ -246,8 +201,7 @@     , _cdsfrrsResponseStatus = pResponseStatus_     } --- | A user-supplied ID that uniquely identifies the datasource. This value--- should be identical to the value of the 'DataSourceID' in the request.+-- | A user-supplied ID that uniquely identifies the datasource. This value should be identical to the value of the 'DataSourceID' in the request. cdsfrrsDataSourceId :: Lens' CreateDataSourceFromRedshiftResponse (Maybe Text) cdsfrrsDataSourceId = lens _cdsfrrsDataSourceId (\ s a -> s{_cdsfrrsDataSourceId = a});
gen/Network/AWS/MachineLearning/CreateDataSourceFromS3.hs view
@@ -18,40 +18,15 @@ -- Stability   : auto-generated -- Portability : non-portable (GHC extensions) ----- Creates a 'DataSource' object. A 'DataSource' references data that can--- be used to perform < CreateMLModel>, < CreateEvaluation>, or--- < CreateBatchPrediction> operations.+-- Creates a 'DataSource' object. A 'DataSource' references data that can be used to perform < CreateMLModel>, < CreateEvaluation>, or < CreateBatchPrediction> operations. ----- 'CreateDataSourceFromS3' is an asynchronous operation. In response to--- 'CreateDataSourceFromS3', Amazon Machine Learning (Amazon ML)--- immediately returns and sets the 'DataSource' status to 'PENDING'. After--- the 'DataSource' is created and ready for use, Amazon ML sets the--- 'Status' parameter to 'COMPLETED'. 'DataSource' in 'COMPLETED' or--- 'PENDING' status can only be used to perform < CreateMLModel>,--- < CreateEvaluation> or < CreateBatchPrediction> operations.+-- 'CreateDataSourceFromS3' is an asynchronous operation. In response to 'CreateDataSourceFromS3', Amazon Machine Learning (Amazon ML) immediately returns and sets the 'DataSource' status to 'PENDING'. After the 'DataSource' is created and ready for use, Amazon ML sets the 'Status' parameter to 'COMPLETED'. 'DataSource' in 'COMPLETED' or 'PENDING' status can only be used to perform < CreateMLModel>, < CreateEvaluation> or < CreateBatchPrediction> operations. ----- If Amazon ML cannot accept the input source, it sets the 'Status'--- parameter to 'FAILED' and includes an error message in the 'Message'--- attribute of the < GetDataSource> operation response.+-- If Amazon ML cannot accept the input source, it sets the 'Status' parameter to 'FAILED' and includes an error message in the 'Message' attribute of the < GetDataSource> operation response. ----- The observation data used in a 'DataSource' should be ready to use; that--- is, it should have a consistent structure, and missing data values--- should be kept to a minimum. The observation data must reside in one or--- more CSV files in an Amazon Simple Storage Service (Amazon S3) bucket,--- along with a schema that describes the data items by name and type. The--- same schema must be used for all of the data files referenced by the--- 'DataSource'.+-- The observation data used in a 'DataSource' should be ready to use; that is, it should have a consistent structure, and missing data values should be kept to a minimum. The observation data must reside in one or more CSV files in an Amazon Simple Storage Service (Amazon S3) bucket, along with a schema that describes the data items by name and type. The same schema must be used for all of the data files referenced by the 'DataSource'. ----- After the 'DataSource' has been created, it\'s ready to use in--- evaluations and batch predictions. If you plan to use the 'DataSource'--- to train an 'MLModel', the 'DataSource' requires another item: a recipe.--- A recipe describes the observation variables that participate in--- training an 'MLModel'. A recipe describes how each input variable will--- be used in training. Will the variable be included or excluded from--- training? Will the variable be manipulated, for example, combined with--- another variable, or split apart into word combinations? The recipe--- provides answers to these questions. For more information, see the--- <http://docs.aws.amazon.com/machine-learning/latest/dg Amazon Machine Learning Developer Guide>.+-- After the 'DataSource' has been created, it\'s ready to use in evaluations and batch predictions. If you plan to use the 'DataSource' to train an 'MLModel', the 'DataSource' requires another item: a recipe. A recipe describes the observation variables that participate in training an 'MLModel'. A recipe describes how each input variable will be used in training. Will the variable be included or excluded from training? Will the variable be manipulated, for example, combined with another variable, or split apart into word combinations? The recipe provides answers to these questions. For more information, see the <http://docs.aws.amazon.com/machine-learning/latest/dg Amazon Machine Learning Developer Guide>. module Network.AWS.MachineLearning.CreateDataSourceFromS3     (     -- * Creating a Request@@ -113,11 +88,7 @@ cdsfsDataSourceName :: Lens' CreateDataSourceFromS3 (Maybe Text) cdsfsDataSourceName = lens _cdsfsDataSourceName (\ s a -> s{_cdsfsDataSourceName = a}); --- | The compute statistics for a 'DataSource'. The statistics are generated--- from the observation data referenced by a 'DataSource'. Amazon ML uses--- the statistics internally during an 'MLModel' training. This parameter--- must be set to 'true' if the ''DataSource'' needs to be used for--- 'MLModel' training+-- | The compute statistics for a 'DataSource'. The statistics are generated from the observation data referenced by a 'DataSource'. Amazon ML uses the statistics internally during an 'MLModel' training. This parameter must be set to 'true' if the ''DataSource'' needs to be used for 'MLModel' training cdsfsComputeStatistics :: Lens' CreateDataSourceFromS3 (Maybe Bool) cdsfsComputeStatistics = lens _cdsfsComputeStatistics (\ s a -> s{_cdsfsComputeStatistics = a}); @@ -127,19 +98,15 @@  -- | The data specification of a 'DataSource': ----- -   DataLocationS3 - Amazon Simple Storage Service (Amazon S3) location---     of the observation data.+-- -   DataLocationS3 - Amazon Simple Storage Service (Amazon S3) location of the observation data. -- -- -   DataSchemaLocationS3 - Amazon S3 location of the 'DataSchema'. ----- -   DataSchema - A JSON string representing the schema. This is not---     required if 'DataSchemaUri' is specified.+-- -   DataSchema - A JSON string representing the schema. This is not required if 'DataSchemaUri' is specified. ----- -   DataRearrangement - A JSON string representing the splitting---     requirement of a 'Datasource'.+-- -   DataRearrangement - A JSON string representing the splitting requirement of a 'Datasource'. -----     Sample ----     ' \"{\\\"splitting\\\":{\\\"percentBegin\\\":10,\\\"percentEnd\\\":60}}\"'+--     Sample - ' \"{\\\"splitting\\\":{\\\"percentBegin\\\":10,\\\"percentEnd\\\":60}}\"' -- cdsfsDataSpec :: Lens' CreateDataSourceFromS3 S3DataSpec cdsfsDataSpec = lens _cdsfsDataSpec (\ s a -> s{_cdsfsDataSpec = a});@@ -183,12 +150,9 @@ instance ToQuery CreateDataSourceFromS3 where         toQuery = const mempty --- | Represents the output of a < CreateDataSourceFromS3> operation, and is--- an acknowledgement that Amazon ML received the request.+-- | Represents the output of a < CreateDataSourceFromS3> operation, and is an acknowledgement that Amazon ML received the request. ----- The < CreateDataSourceFromS3> operation is asynchronous. You can poll--- for updates by using the < GetBatchPrediction> operation and checking--- the 'Status' parameter.+-- The < CreateDataSourceFromS3> operation is asynchronous. You can poll for updates by using the < GetBatchPrediction> operation and checking the 'Status' parameter. -- -- /See:/ 'createDataSourceFromS3Response' smart constructor. data CreateDataSourceFromS3Response = CreateDataSourceFromS3Response'@@ -212,8 +176,7 @@     , _cdsfsrsResponseStatus = pResponseStatus_     } --- | A user-supplied ID that uniquely identifies the datasource. This value--- should be identical to the value of the 'DataSourceID' in the request.+-- | A user-supplied ID that uniquely identifies the datasource. This value should be identical to the value of the 'DataSourceID' in the request. cdsfsrsDataSourceId :: Lens' CreateDataSourceFromS3Response (Maybe Text) cdsfsrsDataSourceId = lens _cdsfsrsDataSourceId (\ s a -> s{_cdsfsrsDataSourceId = a});
gen/Network/AWS/MachineLearning/CreateEvaluation.hs view
@@ -18,24 +18,11 @@ -- Stability   : auto-generated -- Portability : non-portable (GHC extensions) ----- Creates a new 'Evaluation' of an 'MLModel'. An 'MLModel' is evaluated on--- a set of observations associated to a 'DataSource'. Like a 'DataSource'--- for an 'MLModel', the 'DataSource' for an 'Evaluation' contains values--- for the Target Variable. The 'Evaluation' compares the predicted result--- for each observation to the actual outcome and provides a summary so--- that you know how effective the 'MLModel' functions on the test data.--- Evaluation generates a relevant performance metric such as BinaryAUC,--- RegressionRMSE or MulticlassAvgFScore based on the corresponding--- 'MLModelType': 'BINARY', 'REGRESSION' or 'MULTICLASS'.+-- Creates a new 'Evaluation' of an 'MLModel'. An 'MLModel' is evaluated on a set of observations associated to a 'DataSource'. Like a 'DataSource' for an 'MLModel', the 'DataSource' for an 'Evaluation' contains values for the Target Variable. The 'Evaluation' compares the predicted result for each observation to the actual outcome and provides a summary so that you know how effective the 'MLModel' functions on the test data. Evaluation generates a relevant performance metric such as BinaryAUC, RegressionRMSE or MulticlassAvgFScore based on the corresponding 'MLModelType': 'BINARY', 'REGRESSION' or 'MULTICLASS'. ----- 'CreateEvaluation' is an asynchronous operation. In response to--- 'CreateEvaluation', Amazon Machine Learning (Amazon ML) immediately--- returns and sets the evaluation status to 'PENDING'. After the--- 'Evaluation' is created and ready for use, Amazon ML sets the status to--- 'COMPLETED'.+-- 'CreateEvaluation' is an asynchronous operation. In response to 'CreateEvaluation', Amazon Machine Learning (Amazon ML) immediately returns and sets the evaluation status to 'PENDING'. After the 'Evaluation' is created and ready for use, Amazon ML sets the status to 'COMPLETED'. ----- You can use the < GetEvaluation> operation to check progress of the--- evaluation during the creation operation.+-- You can use the < GetEvaluation> operation to check progress of the evaluation during the creation operation. module Network.AWS.MachineLearning.CreateEvaluation     (     -- * Creating a Request@@ -104,13 +91,11 @@  -- | The ID of the 'MLModel' to evaluate. ----- The schema used in creating the 'MLModel' must match the schema of the--- 'DataSource' used in the 'Evaluation'.+-- The schema used in creating the 'MLModel' must match the schema of the 'DataSource' used in the 'Evaluation'. ceMLModelId :: Lens' CreateEvaluation Text ceMLModelId = lens _ceMLModelId (\ s a -> s{_ceMLModelId = a}); --- | The ID of the 'DataSource' for the evaluation. The schema of the--- 'DataSource' must match the schema used to create the 'MLModel'.+-- | The ID of the 'DataSource' for the evaluation. The schema of the 'DataSource' must match the schema used to create the 'MLModel'. ceEvaluationDataSourceId :: Lens' CreateEvaluation Text ceEvaluationDataSourceId = lens _ceEvaluationDataSourceId (\ s a -> s{_ceEvaluationDataSourceId = a}); @@ -153,12 +138,9 @@ instance ToQuery CreateEvaluation where         toQuery = const mempty --- | Represents the output of a < CreateEvaluation> operation, and is an--- acknowledgement that Amazon ML received the request.+-- | Represents the output of a < CreateEvaluation> operation, and is an acknowledgement that Amazon ML received the request. ----- < CreateEvaluation> operation is asynchronous. You can poll for status--- updates by using the < GetEvaluation> operation and checking the--- 'Status' parameter.+-- < CreateEvaluation> operation is asynchronous. You can poll for status updates by using the < GetEvaluation> operation and checking the 'Status' parameter. -- -- /See:/ 'createEvaluationResponse' smart constructor. data CreateEvaluationResponse = CreateEvaluationResponse'@@ -182,9 +164,7 @@     , _cersResponseStatus = pResponseStatus_     } --- | The user-supplied ID that uniquely identifies the 'Evaluation'. This--- value should be identical to the value of the 'EvaluationId' in the--- request.+-- | The user-supplied ID that uniquely identifies the 'Evaluation'. This value should be identical to the value of the 'EvaluationId' in the request. cersEvaluationId :: Lens' CreateEvaluationResponse (Maybe Text) cersEvaluationId = lens _cersEvaluationId (\ s a -> s{_cersEvaluationId = a});
gen/Network/AWS/MachineLearning/CreateMLModel.hs view
@@ -18,25 +18,15 @@ -- Stability   : auto-generated -- Portability : non-portable (GHC extensions) ----- Creates a new 'MLModel' using the data files and the recipe as--- information sources.+-- Creates a new 'MLModel' using the data files and the recipe as information sources. ----- An 'MLModel' is nearly immutable. Users can only update the--- 'MLModelName' and the 'ScoreThreshold' in an 'MLModel' without creating--- a new 'MLModel'.+-- An 'MLModel' is nearly immutable. Users can only update the 'MLModelName' and the 'ScoreThreshold' in an 'MLModel' without creating a new 'MLModel'. ----- 'CreateMLModel' is an asynchronous operation. In response to--- 'CreateMLModel', Amazon Machine Learning (Amazon ML) immediately returns--- and sets the 'MLModel' status to 'PENDING'. After the 'MLModel' is--- created and ready for use, Amazon ML sets the status to 'COMPLETED'.+-- 'CreateMLModel' is an asynchronous operation. In response to 'CreateMLModel', Amazon Machine Learning (Amazon ML) immediately returns and sets the 'MLModel' status to 'PENDING'. After the 'MLModel' is created and ready for use, Amazon ML sets the status to 'COMPLETED'. ----- You can use the < GetMLModel> operation to check progress of the--- 'MLModel' during the creation operation.+-- You can use the < GetMLModel> operation to check progress of the 'MLModel' during the creation operation. ----- < CreateMLModel> requires a 'DataSource' with computed statistics, which--- can be created by setting 'ComputeStatistics' to 'true' in--- < CreateDataSourceFromRDS>, < CreateDataSourceFromS3>, or--- < CreateDataSourceFromRedshift> operations.+-- < CreateMLModel> requires a 'DataSource' with computed statistics, which can be created by setting 'ComputeStatistics' to 'true' in < CreateDataSourceFromRDS>, < CreateDataSourceFromS3>, or < CreateDataSourceFromRedshift> operations. module Network.AWS.MachineLearning.CreateMLModel     (     -- * Creating a Request@@ -110,16 +100,11 @@     , _cmlmTrainingDataSourceId = pTrainingDataSourceId_     } --- | The data recipe for creating 'MLModel'. You must specify either the--- recipe or its URI. If you don’t specify a recipe or its URI, Amazon ML--- creates a default.+-- | The data recipe for creating 'MLModel'. You must specify either the recipe or its URI. If you don’t specify a recipe or its URI, Amazon ML creates a default. cmlmRecipe :: Lens' CreateMLModel (Maybe Text) cmlmRecipe = lens _cmlmRecipe (\ s a -> s{_cmlmRecipe = a}); --- | The Amazon Simple Storage Service (Amazon S3) location and file name--- that contains the 'MLModel' recipe. You must specify either the recipe--- or its URI. If you don’t specify a recipe or its URI, Amazon ML creates--- a default.+-- | The Amazon Simple Storage Service (Amazon S3) location and file name that contains the 'MLModel' recipe. You must specify either the recipe or its URI. If you don’t specify a recipe or its URI, Amazon ML creates a default. cmlmRecipeURI :: Lens' CreateMLModel (Maybe Text) cmlmRecipeURI = lens _cmlmRecipeURI (\ s a -> s{_cmlmRecipeURI = a}); @@ -127,41 +112,23 @@ cmlmMLModelName :: Lens' CreateMLModel (Maybe Text) cmlmMLModelName = lens _cmlmMLModelName (\ s a -> s{_cmlmMLModelName = a}); --- | A list of the training parameters in the 'MLModel'. The list is--- implemented as a map of key\/value pairs.+-- | A list of the training parameters in the 'MLModel'. The list is implemented as a map of key\/value pairs. -- -- The following is the current set of training parameters: ----- -   'sgd.l1RegularizationAmount' - Coefficient regularization L1 norm.---     It controls overfitting the data by penalizing large coefficients.---     This tends to drive coefficients to zero, resulting in sparse---     feature set. If you use this parameter, start by specifying a small---     value such as 1.0E-08.+-- -   'sgd.l1RegularizationAmount' - Coefficient regularization L1 norm. It controls overfitting the data by penalizing large coefficients. This tends to drive coefficients to zero, resulting in sparse feature set. If you use this parameter, start by specifying a small value such as 1.0E-08. -----     The value is a double that ranges from 0 to MAX_DOUBLE. The default---     is not to use L1 normalization. The parameter cannot be used when---     'L2' is specified. Use this parameter sparingly.+--     The value is a double that ranges from 0 to MAX_DOUBLE. The default is not to use L1 normalization. The parameter cannot be used when 'L2' is specified. Use this parameter sparingly. ----- -   'sgd.l2RegularizationAmount' - Coefficient regularization L2 norm.---     It controls overfitting the data by penalizing large coefficients.---     This tends to drive coefficients to small, nonzero values. If you---     use this parameter, start by specifying a small value such as---     1.0E-08.+-- -   'sgd.l2RegularizationAmount' - Coefficient regularization L2 norm. It controls overfitting the data by penalizing large coefficients. This tends to drive coefficients to small, nonzero values. If you use this parameter, start by specifying a small value such as 1.0E-08. -----     The valuseis a double that ranges from 0 to MAX_DOUBLE. The default---     is not to use L2 normalization. This cannot be used when 'L1' is---     specified. Use this parameter sparingly.+--     The valuseis a double that ranges from 0 to MAX_DOUBLE. The default is not to use L2 normalization. This cannot be used when 'L1' is specified. Use this parameter sparingly. ----- -   'sgd.maxPasses' - Number of times that the training process---     traverses the observations to build the 'MLModel'. The value is an---     integer that ranges from 1 to 10000. The default value is 10.+-- -   'sgd.maxPasses' - Number of times that the training process traverses the observations to build the 'MLModel'. The value is an integer that ranges from 1 to 10000. The default value is 10. ----- -   'sgd.maxMLModelSizeInBytes' - Maximum allowed size of the model.---     Depending on the input data, the size of the model might affect its---     performance.+-- -   'sgd.maxMLModelSizeInBytes' - Maximum allowed size of the model. Depending on the input data, the size of the model might affect its performance. -----     The value is an integer that ranges from 100000 to 2147483648. The---     default value is 33554432.+--     The value is an integer that ranges from 100000 to 2147483648. The default value is 33554432. -- cmlmParameters :: Lens' CreateMLModel (HashMap Text Text) cmlmParameters = lens _cmlmParameters (\ s a -> s{_cmlmParameters = a}) . _Default . _Map;@@ -170,17 +137,13 @@ cmlmMLModelId :: Lens' CreateMLModel Text cmlmMLModelId = lens _cmlmMLModelId (\ s a -> s{_cmlmMLModelId = a}); --- | The category of supervised learning that this 'MLModel' will address.--- Choose from the following types:+-- | The category of supervised learning that this 'MLModel' will address. Choose from the following types: ----- -   Choose 'REGRESSION' if the 'MLModel' will be used to predict a---     numeric value.+-- -   Choose 'REGRESSION' if the 'MLModel' will be used to predict a numeric value. -- -   Choose 'BINARY' if the 'MLModel' result has two possible values.--- -   Choose 'MULTICLASS' if the 'MLModel' result has a limited number of---     values.+-- -   Choose 'MULTICLASS' if the 'MLModel' result has a limited number of values. ----- For more information, see the--- <http://docs.aws.amazon.com/machine-learning/latest/dg Amazon Machine Learning Developer Guide>.+-- For more information, see the <http://docs.aws.amazon.com/machine-learning/latest/dg Amazon Machine Learning Developer Guide>. cmlmMLModelType :: Lens' CreateMLModel MLModelType cmlmMLModelType = lens _cmlmMLModelType (\ s a -> s{_cmlmMLModelType = a}); @@ -230,12 +193,9 @@ instance ToQuery CreateMLModel where         toQuery = const mempty --- | Represents the output of a < CreateMLModel> operation, and is an--- acknowledgement that Amazon ML received the request.+-- | Represents the output of a < CreateMLModel> operation, and is an acknowledgement that Amazon ML received the request. ----- The < CreateMLModel> operation is asynchronous. You can poll for status--- updates by using the < GetMLModel> operation and checking the 'Status'--- parameter.+-- The < CreateMLModel> operation is asynchronous. You can poll for status updates by using the < GetMLModel> operation and checking the 'Status' parameter. -- -- /See:/ 'createMLModelResponse' smart constructor. data CreateMLModelResponse = CreateMLModelResponse'@@ -259,8 +219,7 @@     , _cmlmrsResponseStatus = pResponseStatus_     } --- | A user-supplied ID that uniquely identifies the 'MLModel'. This value--- should be identical to the value of the 'MLModelId' in the request.+-- | A user-supplied ID that uniquely identifies the 'MLModel'. This value should be identical to the value of the 'MLModelId' in the request. cmlmrsMLModelId :: Lens' CreateMLModelResponse (Maybe Text) cmlmrsMLModelId = lens _cmlmrsMLModelId (\ s a -> s{_cmlmrsMLModelId = a});
gen/Network/AWS/MachineLearning/CreateRealtimeEndpoint.hs view
@@ -18,9 +18,7 @@ -- Stability   : auto-generated -- Portability : non-portable (GHC extensions) ----- Creates a real-time endpoint for the 'MLModel'. The endpoint contains--- the URI of the 'MLModel'; that is, the location to send real-time--- prediction requests for the specified 'MLModel'.+-- Creates a real-time endpoint for the 'MLModel'. The endpoint contains the URI of the 'MLModel'; that is, the location to send real-time prediction requests for the specified 'MLModel'. module Network.AWS.MachineLearning.CreateRealtimeEndpoint     (     -- * Creating a Request@@ -106,11 +104,9 @@  -- | Represents the output of an < CreateRealtimeEndpoint> operation. ----- The result contains the 'MLModelId' and the endpoint information for the--- 'MLModel'.+-- The result contains the 'MLModelId' and the endpoint information for the 'MLModel'. ----- The endpoint information includes the URI of the 'MLModel'; that is, the--- location to send online prediction requests for the specified 'MLModel'.+-- The endpoint information includes the URI of the 'MLModel'; that is, the location to send online prediction requests for the specified 'MLModel'. -- -- /See:/ 'createRealtimeEndpointResponse' smart constructor. data CreateRealtimeEndpointResponse = CreateRealtimeEndpointResponse'@@ -142,8 +138,7 @@ crersRealtimeEndpointInfo :: Lens' CreateRealtimeEndpointResponse (Maybe RealtimeEndpointInfo) crersRealtimeEndpointInfo = lens _crersRealtimeEndpointInfo (\ s a -> s{_crersRealtimeEndpointInfo = a}); --- | A user-supplied ID that uniquely identifies the 'MLModel'. This value--- should be identical to the value of the 'MLModelId' in the request.+-- | A user-supplied ID that uniquely identifies the 'MLModel'. This value should be identical to the value of the 'MLModelId' in the request. crersMLModelId :: Lens' CreateRealtimeEndpointResponse (Maybe Text) crersMLModelId = lens _crersMLModelId (\ s a -> s{_crersMLModelId = a});
gen/Network/AWS/MachineLearning/DeleteBatchPrediction.hs view
@@ -18,15 +18,11 @@ -- Stability   : auto-generated -- Portability : non-portable (GHC extensions) ----- Assigns the DELETED status to a 'BatchPrediction', rendering it--- unusable.+-- Assigns the DELETED status to a 'BatchPrediction', rendering it unusable. ----- After using the 'DeleteBatchPrediction' operation, you can use the--- < GetBatchPrediction> operation to verify that the status of the--- 'BatchPrediction' changed to DELETED.+-- After using the 'DeleteBatchPrediction' operation, you can use the < GetBatchPrediction> operation to verify that the status of the 'BatchPrediction' changed to DELETED. ----- __Caution:__ The result of the 'DeleteBatchPrediction' operation is--- irreversible.+-- __Caution:__ The result of the 'DeleteBatchPrediction' operation is irreversible. module Network.AWS.MachineLearning.DeleteBatchPrediction     (     -- * Creating a Request@@ -111,9 +107,7 @@  -- | Represents the output of a < DeleteBatchPrediction> operation. ----- You can use the < GetBatchPrediction> operation and check the value of--- the 'Status' parameter to see whether a 'BatchPrediction' is marked as--- 'DELETED'.+-- You can use the < GetBatchPrediction> operation and check the value of the 'Status' parameter to see whether a 'BatchPrediction' is marked as 'DELETED'. -- -- /See:/ 'deleteBatchPredictionResponse' smart constructor. data DeleteBatchPredictionResponse = DeleteBatchPredictionResponse'@@ -137,9 +131,7 @@     , _dbprsResponseStatus = pResponseStatus_     } --- | A user-supplied ID that uniquely identifies the 'BatchPrediction'. This--- value should be identical to the value of the 'BatchPredictionID' in the--- request.+-- | A user-supplied ID that uniquely identifies the 'BatchPrediction'. This value should be identical to the value of the 'BatchPredictionID' in the request. dbprsBatchPredictionId :: Lens' DeleteBatchPredictionResponse (Maybe Text) dbprsBatchPredictionId = lens _dbprsBatchPredictionId (\ s a -> s{_dbprsBatchPredictionId = a});
gen/Network/AWS/MachineLearning/DeleteDataSource.hs view
@@ -20,12 +20,9 @@ -- -- Assigns the DELETED status to a 'DataSource', rendering it unusable. ----- After using the 'DeleteDataSource' operation, you can use the--- < GetDataSource> operation to verify that the status of the 'DataSource'--- changed to DELETED.+-- After using the 'DeleteDataSource' operation, you can use the < GetDataSource> operation to verify that the status of the 'DataSource' changed to DELETED. ----- __Caution:__ The results of the 'DeleteDataSource' operation are--- irreversible.+-- __Caution:__ The results of the 'DeleteDataSource' operation are irreversible. module Network.AWS.MachineLearning.DeleteDataSource     (     -- * Creating a Request@@ -129,8 +126,7 @@     , _ddsrsResponseStatus = pResponseStatus_     } --- | A user-supplied ID that uniquely identifies the 'DataSource'. This value--- should be identical to the value of the 'DataSourceID' in the request.+-- | A user-supplied ID that uniquely identifies the 'DataSource'. This value should be identical to the value of the 'DataSourceID' in the request. ddsrsDataSourceId :: Lens' DeleteDataSourceResponse (Maybe Text) ddsrsDataSourceId = lens _ddsrsDataSourceId (\ s a -> s{_ddsrsDataSourceId = a});
gen/Network/AWS/MachineLearning/DeleteEvaluation.hs view
@@ -20,12 +20,9 @@ -- -- Assigns the 'DELETED' status to an 'Evaluation', rendering it unusable. ----- After invoking the 'DeleteEvaluation' operation, you can use the--- < GetEvaluation> operation to verify that the status of the 'Evaluation'--- changed to 'DELETED'.+-- After invoking the 'DeleteEvaluation' operation, you can use the < GetEvaluation> operation to verify that the status of the 'Evaluation' changed to 'DELETED'. ----- __Caution:__ The results of the 'DeleteEvaluation' operation are--- irreversible.+-- __Caution:__ The results of the 'DeleteEvaluation' operation are irreversible. module Network.AWS.MachineLearning.DeleteEvaluation     (     -- * Creating a Request@@ -105,12 +102,9 @@ instance ToQuery DeleteEvaluation where         toQuery = const mempty --- | Represents the output of a < DeleteEvaluation> operation. The output--- indicates that Amazon Machine Learning (Amazon ML) received the request.+-- | Represents the output of a < DeleteEvaluation> operation. The output indicates that Amazon Machine Learning (Amazon ML) received the request. ----- You can use the < GetEvaluation> operation and check the value of the--- 'Status' parameter to see whether an 'Evaluation' is marked as--- 'DELETED'.+-- You can use the < GetEvaluation> operation and check the value of the 'Status' parameter to see whether an 'Evaluation' is marked as 'DELETED'. -- -- /See:/ 'deleteEvaluationResponse' smart constructor. data DeleteEvaluationResponse = DeleteEvaluationResponse'@@ -134,8 +128,7 @@     , _dersResponseStatus = pResponseStatus_     } --- | A user-supplied ID that uniquely identifies the 'Evaluation'. This value--- should be identical to the value of the 'EvaluationId' in the request.+-- | A user-supplied ID that uniquely identifies the 'Evaluation'. This value should be identical to the value of the 'EvaluationId' in the request. dersEvaluationId :: Lens' DeleteEvaluationResponse (Maybe Text) dersEvaluationId = lens _dersEvaluationId (\ s a -> s{_dersEvaluationId = a});
gen/Network/AWS/MachineLearning/DeleteMLModel.hs view
@@ -20,11 +20,9 @@ -- -- Assigns the DELETED status to an 'MLModel', rendering it unusable. ----- After using the 'DeleteMLModel' operation, you can use the < GetMLModel>--- operation to verify that the status of the 'MLModel' changed to DELETED.+-- After using the 'DeleteMLModel' operation, you can use the < GetMLModel> operation to verify that the status of the 'MLModel' changed to DELETED. ----- __Caution:__ The result of the 'DeleteMLModel' operation is--- irreversible.+-- __Caution:__ The result of the 'DeleteMLModel' operation is irreversible. module Network.AWS.MachineLearning.DeleteMLModel     (     -- * Creating a Request@@ -105,8 +103,7 @@  -- | Represents the output of a < DeleteMLModel> operation. ----- You can use the < GetMLModel> operation and check the value of the--- 'Status' parameter to see whether an 'MLModel' is marked as 'DELETED'.+-- You can use the < GetMLModel> operation and check the value of the 'Status' parameter to see whether an 'MLModel' is marked as 'DELETED'. -- -- /See:/ 'deleteMLModelResponse' smart constructor. data DeleteMLModelResponse = DeleteMLModelResponse'@@ -130,8 +127,7 @@     , _dmlmrsResponseStatus = pResponseStatus_     } --- | A user-supplied ID that uniquely identifies the 'MLModel'. This value--- should be identical to the value of the 'MLModelID' in the request.+-- | A user-supplied ID that uniquely identifies the 'MLModel'. This value should be identical to the value of the 'MLModelID' in the request. dmlmrsMLModelId :: Lens' DeleteMLModelResponse (Maybe Text) dmlmrsMLModelId = lens _dmlmrsMLModelId (\ s a -> s{_dmlmrsMLModelId = a});
gen/Network/AWS/MachineLearning/DeleteRealtimeEndpoint.hs view
@@ -104,8 +104,7 @@  -- | Represents the output of an < DeleteRealtimeEndpoint> operation. ----- The result contains the 'MLModelId' and the endpoint information for the--- 'MLModel'.+-- The result contains the 'MLModelId' and the endpoint information for the 'MLModel'. -- -- /See:/ 'deleteRealtimeEndpointResponse' smart constructor. data DeleteRealtimeEndpointResponse = DeleteRealtimeEndpointResponse'@@ -137,8 +136,7 @@ drersRealtimeEndpointInfo :: Lens' DeleteRealtimeEndpointResponse (Maybe RealtimeEndpointInfo) drersRealtimeEndpointInfo = lens _drersRealtimeEndpointInfo (\ s a -> s{_drersRealtimeEndpointInfo = a}); --- | A user-supplied ID that uniquely identifies the 'MLModel'. This value--- should be identical to the value of the 'MLModelId' in the request.+-- | A user-supplied ID that uniquely identifies the 'MLModel'. This value should be identical to the value of the 'MLModelId' in the request. drersMLModelId :: Lens' DeleteRealtimeEndpointResponse (Maybe Text) drersMLModelId = lens _drersMLModelId (\ s a -> s{_drersMLModelId = a});
gen/Network/AWS/MachineLearning/DescribeBatchPredictions.hs view
@@ -18,8 +18,7 @@ -- Stability   : auto-generated -- Portability : non-portable (GHC extensions) ----- Returns a list of 'BatchPrediction' operations that match the search--- criteria in the request.+-- Returns a list of 'BatchPrediction' operations that match the search criteria in the request. -- -- This operation returns paginated results. module Network.AWS.MachineLearning.DescribeBatchPredictions@@ -114,25 +113,17 @@     , _dbpLE = Nothing     } --- | The equal to operator. The 'BatchPrediction' results will have--- 'FilterVariable' values that exactly match the value specified with--- 'EQ'.+-- | The equal to operator. The 'BatchPrediction' results will have 'FilterVariable' values that exactly match the value specified with 'EQ'. dbpEQ :: Lens' DescribeBatchPredictions (Maybe Text) dbpEQ = lens _dbpEQ (\ s a -> s{_dbpEQ = a}); --- | The greater than or equal to operator. The 'BatchPrediction' results--- will have 'FilterVariable' values that are greater than or equal to the--- value specified with 'GE'.+-- | The greater than or equal to operator. The 'BatchPrediction' results will have 'FilterVariable' values that are greater than or equal to the value specified with 'GE'. dbpGE :: Lens' DescribeBatchPredictions (Maybe Text) dbpGE = lens _dbpGE (\ s a -> s{_dbpGE = a}); --- | A string that is found at the beginning of a variable, such as 'Name' or--- 'Id'.+-- | A string that is found at the beginning of a variable, such as 'Name' or 'Id'. ----- For example, a 'Batch Prediction' operation could have the 'Name'--- '2014-09-09-HolidayGiftMailer'. To search for this 'BatchPrediction',--- select 'Name' for the 'FilterVariable' and any of the following strings--- for the 'Prefix':+-- For example, a 'Batch Prediction' operation could have the 'Name' '2014-09-09-HolidayGiftMailer'. To search for this 'BatchPrediction', select 'Name' for the 'FilterVariable' and any of the following strings for the 'Prefix': -- -- -   2014-09 --@@ -143,14 +134,11 @@ dbpPrefix :: Lens' DescribeBatchPredictions (Maybe Text) dbpPrefix = lens _dbpPrefix (\ s a -> s{_dbpPrefix = a}); --- | The greater than operator. The 'BatchPrediction' results will have--- 'FilterVariable' values that are greater than the value specified with--- 'GT'.+-- | The greater than operator. The 'BatchPrediction' results will have 'FilterVariable' values that are greater than the value specified with 'GT'. dbpGT :: Lens' DescribeBatchPredictions (Maybe Text) dbpGT = lens _dbpGT (\ s a -> s{_dbpGT = a}); --- | The not equal to operator. The 'BatchPrediction' results will have--- 'FilterVariable' values not equal to the value specified with 'NE'.+-- | The not equal to operator. The 'BatchPrediction' results will have 'FilterVariable' values not equal to the value specified with 'NE'. dbpNE :: Lens' DescribeBatchPredictions (Maybe Text) dbpNE = lens _dbpNE (\ s a -> s{_dbpNE = a}); @@ -158,8 +146,7 @@ dbpNextToken :: Lens' DescribeBatchPredictions (Maybe Text) dbpNextToken = lens _dbpNextToken (\ s a -> s{_dbpNextToken = a}); --- | A two-value parameter that determines the sequence of the resulting list--- of 'MLModel's.+-- | A two-value parameter that determines the sequence of the resulting list of 'MLModel's. -- -- -   'asc' - Arranges the list in ascending order (A-Z, 0-9). -- -   'dsc' - Arranges the list in descending order (Z-A, 9-0).@@ -168,40 +155,27 @@ dbpSortOrder :: Lens' DescribeBatchPredictions (Maybe SortOrder) dbpSortOrder = lens _dbpSortOrder (\ s a -> s{_dbpSortOrder = a}); --- | The number of pages of information to include in the result. The range--- of acceptable values is 1 through 100. The default value is 100.+-- | The number of pages of information to include in the result. The range of acceptable values is 1 through 100. The default value is 100. dbpLimit :: Lens' DescribeBatchPredictions (Maybe Natural) dbpLimit = lens _dbpLimit (\ s a -> s{_dbpLimit = a}) . mapping _Nat; --- | The less than operator. The 'BatchPrediction' results will have--- 'FilterVariable' values that are less than the value specified with--- 'LT'.+-- | The less than operator. The 'BatchPrediction' results will have 'FilterVariable' values that are less than the value specified with 'LT'. dbpLT :: Lens' DescribeBatchPredictions (Maybe Text) dbpLT = lens _dbpLT (\ s a -> s{_dbpLT = a}); --- | Use one of the following variables to filter a list of--- 'BatchPrediction':+-- | Use one of the following variables to filter a list of 'BatchPrediction': ----- -   'CreatedAt' - Sets the search criteria to the 'BatchPrediction'---     creation date.+-- -   'CreatedAt' - Sets the search criteria to the 'BatchPrediction' creation date. -- -   'Status' - Sets the search criteria to the 'BatchPrediction' status.--- -   'Name' - Sets the search criteria to the contents of the---     'BatchPrediction' ____ 'Name'.--- -   'IAMUser' - Sets the search criteria to the user account that---     invoked the 'BatchPrediction' creation.--- -   'MLModelId' - Sets the search criteria to the 'MLModel' used in the---     'BatchPrediction'.--- -   'DataSourceId' - Sets the search criteria to the 'DataSource' used---     in the 'BatchPrediction'.--- -   'DataURI' - Sets the search criteria to the data file(s) used in the---     'BatchPrediction'. The URL can identify either a file or an Amazon---     Simple Storage Solution (Amazon S3) bucket or directory.+-- -   'Name' - Sets the search criteria to the contents of the 'BatchPrediction' ____ 'Name'.+-- -   'IAMUser' - Sets the search criteria to the user account that invoked the 'BatchPrediction' creation.+-- -   'MLModelId' - Sets the search criteria to the 'MLModel' used in the 'BatchPrediction'.+-- -   'DataSourceId' - Sets the search criteria to the 'DataSource' used in the 'BatchPrediction'.+-- -   'DataURI' - Sets the search criteria to the data file(s) used in the 'BatchPrediction'. The URL can identify either a file or an Amazon Simple Storage Solution (Amazon S3) bucket or directory. dbpFilterVariable :: Lens' DescribeBatchPredictions (Maybe BatchPredictionFilterVariable) dbpFilterVariable = lens _dbpFilterVariable (\ s a -> s{_dbpFilterVariable = a}); --- | The less than or equal to operator. The 'BatchPrediction' results will--- have 'FilterVariable' values that are less than or equal to the value--- specified with 'LE'.+-- | The less than or equal to operator. The 'BatchPrediction' results will have 'FilterVariable' values that are less than or equal to the value specified with 'LE'. dbpLE :: Lens' DescribeBatchPredictions (Maybe Text) dbpLE = lens _dbpLE (\ s a -> s{_dbpLE = a}); @@ -256,8 +230,7 @@ instance ToQuery DescribeBatchPredictions where         toQuery = const mempty --- | Represents the output of a < DescribeBatchPredictions> operation. The--- content is essentially a list of 'BatchPrediction's.+-- | Represents the output of a < DescribeBatchPredictions> operation. The content is essentially a list of 'BatchPrediction's. -- -- /See:/ 'describeBatchPredictionsResponse' smart constructor. data DescribeBatchPredictionsResponse = DescribeBatchPredictionsResponse'@@ -289,8 +262,7 @@ drsResults :: Lens' DescribeBatchPredictionsResponse [BatchPrediction] drsResults = lens _drsResults (\ s a -> s{_drsResults = a}) . _Default . _Coerce; --- | The ID of the next page in the paginated results that indicates at least--- one more page follows.+-- | The ID of the next page in the paginated results that indicates at least one more page follows. drsNextToken :: Lens' DescribeBatchPredictionsResponse (Maybe Text) drsNextToken = lens _drsNextToken (\ s a -> s{_drsNextToken = a});
gen/Network/AWS/MachineLearning/DescribeDataSources.hs view
@@ -18,8 +18,7 @@ -- Stability   : auto-generated -- Portability : non-portable (GHC extensions) ----- Returns a list of 'DataSource' that match the search criteria in the--- request.+-- Returns a list of 'DataSource' that match the search criteria in the request. -- -- This operation returns paginated results. module Network.AWS.MachineLearning.DescribeDataSources@@ -114,25 +113,17 @@     , _ddsLE = Nothing     } --- | The equal to operator. The 'DataSource' results will have--- 'FilterVariable' values that exactly match the value specified with--- 'EQ'.+-- | The equal to operator. The 'DataSource' results will have 'FilterVariable' values that exactly match the value specified with 'EQ'. ddsEQ :: Lens' DescribeDataSources (Maybe Text) ddsEQ = lens _ddsEQ (\ s a -> s{_ddsEQ = a}); --- | The greater than or equal to operator. The 'DataSource' results will--- have 'FilterVariable' values that are greater than or equal to the value--- specified with 'GE'.+-- | The greater than or equal to operator. The 'DataSource' results will have 'FilterVariable' values that are greater than or equal to the value specified with 'GE'. ddsGE :: Lens' DescribeDataSources (Maybe Text) ddsGE = lens _ddsGE (\ s a -> s{_ddsGE = a}); --- | A string that is found at the beginning of a variable, such as 'Name' or--- 'Id'.+-- | A string that is found at the beginning of a variable, such as 'Name' or 'Id'. ----- For example, a 'DataSource' could have the 'Name'--- '2014-09-09-HolidayGiftMailer'. To search for this 'DataSource', select--- 'Name' for the 'FilterVariable' and any of the following strings for the--- 'Prefix':+-- For example, a 'DataSource' could have the 'Name' '2014-09-09-HolidayGiftMailer'. To search for this 'DataSource', select 'Name' for the 'FilterVariable' and any of the following strings for the 'Prefix': -- -- -   2014-09 --@@ -143,14 +134,11 @@ ddsPrefix :: Lens' DescribeDataSources (Maybe Text) ddsPrefix = lens _ddsPrefix (\ s a -> s{_ddsPrefix = a}); --- | The greater than operator. The 'DataSource' results will have--- 'FilterVariable' values that are greater than the value specified with--- 'GT'.+-- | The greater than operator. The 'DataSource' results will have 'FilterVariable' values that are greater than the value specified with 'GT'. ddsGT :: Lens' DescribeDataSources (Maybe Text) ddsGT = lens _ddsGT (\ s a -> s{_ddsGT = a}); --- | The not equal to operator. The 'DataSource' results will have--- 'FilterVariable' values not equal to the value specified with 'NE'.+-- | The not equal to operator. The 'DataSource' results will have 'FilterVariable' values not equal to the value specified with 'NE'. ddsNE :: Lens' DescribeDataSources (Maybe Text) ddsNE = lens _ddsNE (\ s a -> s{_ddsNE = a}); @@ -158,8 +146,7 @@ ddsNextToken :: Lens' DescribeDataSources (Maybe Text) ddsNextToken = lens _ddsNextToken (\ s a -> s{_ddsNextToken = a}); --- | A two-value parameter that determines the sequence of the resulting list--- of 'DataSource'.+-- | A two-value parameter that determines the sequence of the resulting list of 'DataSource'. -- -- -   'asc' - Arranges the list in ascending order (A-Z, 0-9). -- -   'dsc' - Arranges the list in descending order (Z-A, 9-0).@@ -172,30 +159,21 @@ ddsLimit :: Lens' DescribeDataSources (Maybe Natural) ddsLimit = lens _ddsLimit (\ s a -> s{_ddsLimit = a}) . mapping _Nat; --- | The less than operator. The 'DataSource' results will have--- 'FilterVariable' values that are less than the value specified with--- 'LT'.+-- | The less than operator. The 'DataSource' results will have 'FilterVariable' values that are less than the value specified with 'LT'. ddsLT :: Lens' DescribeDataSources (Maybe Text) ddsLT = lens _ddsLT (\ s a -> s{_ddsLT = a});  -- | Use one of the following variables to filter a list of 'DataSource': ----- -   'CreatedAt' - Sets the search criteria to 'DataSource' creation---     dates.+-- -   'CreatedAt' - Sets the search criteria to 'DataSource' creation dates. -- -   'Status' - Sets the search criteria to 'DataSource' statuses.--- -   'Name' - Sets the search criteria to the contents of 'DataSource'---     ____ 'Name'.--- -   'DataUri' - Sets the search criteria to the URI of data files used---     to create the 'DataSource'. The URI can identify either a file or an---     Amazon Simple Storage Service (Amazon S3) bucket or directory.--- -   'IAMUser' - Sets the search criteria to the user account that---     invoked the 'DataSource' creation.+-- -   'Name' - Sets the search criteria to the contents of 'DataSource' ____ 'Name'.+-- -   'DataUri' - Sets the search criteria to the URI of data files used to create the 'DataSource'. The URI can identify either a file or an Amazon Simple Storage Service (Amazon S3) bucket or directory.+-- -   'IAMUser' - Sets the search criteria to the user account that invoked the 'DataSource' creation. ddsFilterVariable :: Lens' DescribeDataSources (Maybe DataSourceFilterVariable) ddsFilterVariable = lens _ddsFilterVariable (\ s a -> s{_ddsFilterVariable = a}); --- | The less than or equal to operator. The 'DataSource' results will have--- 'FilterVariable' values that are less than or equal to the value--- specified with 'LE'.+-- | The less than or equal to operator. The 'DataSource' results will have 'FilterVariable' values that are less than or equal to the value specified with 'LE'. ddsLE :: Lens' DescribeDataSources (Maybe Text) ddsLE = lens _ddsLE (\ s a -> s{_ddsLE = a}); @@ -250,8 +228,7 @@ instance ToQuery DescribeDataSources where         toQuery = const mempty --- | Represents the query results from a < DescribeDataSources> operation.--- The content is essentially a list of 'DataSource'.+-- | Represents the query results from a < DescribeDataSources> operation. The content is essentially a list of 'DataSource'. -- -- /See:/ 'describeDataSourcesResponse' smart constructor. data DescribeDataSourcesResponse = DescribeDataSourcesResponse'@@ -283,8 +260,7 @@ ddssrsResults :: Lens' DescribeDataSourcesResponse [DataSource] ddssrsResults = lens _ddssrsResults (\ s a -> s{_ddssrsResults = a}) . _Default . _Coerce; --- | An ID of the next page in the paginated results that indicates at least--- one more page follows.+-- | An ID of the next page in the paginated results that indicates at least one more page follows. ddssrsNextToken :: Lens' DescribeDataSourcesResponse (Maybe Text) ddssrsNextToken = lens _ddssrsNextToken (\ s a -> s{_ddssrsNextToken = a});
gen/Network/AWS/MachineLearning/DescribeEvaluations.hs view
@@ -18,8 +18,7 @@ -- Stability   : auto-generated -- Portability : non-portable (GHC extensions) ----- Returns a list of 'DescribeEvaluations' that match the search criteria--- in the request.+-- Returns a list of 'DescribeEvaluations' that match the search criteria in the request. -- -- This operation returns paginated results. module Network.AWS.MachineLearning.DescribeEvaluations@@ -114,25 +113,17 @@     , _deLE = Nothing     } --- | The equal to operator. The 'Evaluation' results will have--- 'FilterVariable' values that exactly match the value specified with--- 'EQ'.+-- | The equal to operator. The 'Evaluation' results will have 'FilterVariable' values that exactly match the value specified with 'EQ'. deEQ :: Lens' DescribeEvaluations (Maybe Text) deEQ = lens _deEQ (\ s a -> s{_deEQ = a}); --- | The greater than or equal to operator. The 'Evaluation' results will--- have 'FilterVariable' values that are greater than or equal to the value--- specified with 'GE'.+-- | The greater than or equal to operator. The 'Evaluation' results will have 'FilterVariable' values that are greater than or equal to the value specified with 'GE'. deGE :: Lens' DescribeEvaluations (Maybe Text) deGE = lens _deGE (\ s a -> s{_deGE = a}); --- | A string that is found at the beginning of a variable, such as 'Name' or--- 'Id'.+-- | A string that is found at the beginning of a variable, such as 'Name' or 'Id'. ----- For example, an 'Evaluation' could have the 'Name'--- '2014-09-09-HolidayGiftMailer'. To search for this 'Evaluation', select--- 'Name' for the 'FilterVariable' and any of the following strings for the--- 'Prefix':+-- For example, an 'Evaluation' could have the 'Name' '2014-09-09-HolidayGiftMailer'. To search for this 'Evaluation', select 'Name' for the 'FilterVariable' and any of the following strings for the 'Prefix': -- -- -   2014-09 --@@ -143,14 +134,11 @@ dePrefix :: Lens' DescribeEvaluations (Maybe Text) dePrefix = lens _dePrefix (\ s a -> s{_dePrefix = a}); --- | The greater than operator. The 'Evaluation' results will have--- 'FilterVariable' values that are greater than the value specified with--- 'GT'.+-- | The greater than operator. The 'Evaluation' results will have 'FilterVariable' values that are greater than the value specified with 'GT'. deGT :: Lens' DescribeEvaluations (Maybe Text) deGT = lens _deGT (\ s a -> s{_deGT = a}); --- | The not equal to operator. The 'Evaluation' results will have--- 'FilterVariable' values not equal to the value specified with 'NE'.+-- | The not equal to operator. The 'Evaluation' results will have 'FilterVariable' values not equal to the value specified with 'NE'. deNE :: Lens' DescribeEvaluations (Maybe Text) deNE = lens _deNE (\ s a -> s{_deNE = a}); @@ -158,8 +146,7 @@ deNextToken :: Lens' DescribeEvaluations (Maybe Text) deNextToken = lens _deNextToken (\ s a -> s{_deNextToken = a}); --- | A two-value parameter that determines the sequence of the resulting list--- of 'Evaluation'.+-- | A two-value parameter that determines the sequence of the resulting list of 'Evaluation'. -- -- -   'asc' - Arranges the list in ascending order (A-Z, 0-9). -- -   'dsc' - Arranges the list in descending order (Z-A, 9-0).@@ -172,35 +159,23 @@ deLimit :: Lens' DescribeEvaluations (Maybe Natural) deLimit = lens _deLimit (\ s a -> s{_deLimit = a}) . mapping _Nat; --- | The less than operator. The 'Evaluation' results will have--- 'FilterVariable' values that are less than the value specified with--- 'LT'.+-- | The less than operator. The 'Evaluation' results will have 'FilterVariable' values that are less than the value specified with 'LT'. deLT :: Lens' DescribeEvaluations (Maybe Text) deLT = lens _deLT (\ s a -> s{_deLT = a}); --- | Use one of the following variable to filter a list of 'Evaluation'--- objects:+-- | Use one of the following variable to filter a list of 'Evaluation' objects: ----- -   'CreatedAt' - Sets the search criteria to the 'Evaluation' creation---     date.+-- -   'CreatedAt' - Sets the search criteria to the 'Evaluation' creation date. -- -   'Status' - Sets the search criteria to the 'Evaluation' status.--- -   'Name' - Sets the search criteria to the contents of 'Evaluation'---     ____ 'Name'.--- -   'IAMUser' - Sets the search criteria to the user account that---     invoked an 'Evaluation'.--- -   'MLModelId' - Sets the search criteria to the 'MLModel' that was---     evaluated.--- -   'DataSourceId' - Sets the search criteria to the 'DataSource' used---     in 'Evaluation'.--- -   'DataUri' - Sets the search criteria to the data file(s) used in---     'Evaluation'. The URL can identify either a file or an Amazon Simple---     Storage Solution (Amazon S3) bucket or directory.+-- -   'Name' - Sets the search criteria to the contents of 'Evaluation' ____ 'Name'.+-- -   'IAMUser' - Sets the search criteria to the user account that invoked an 'Evaluation'.+-- -   'MLModelId' - Sets the search criteria to the 'MLModel' that was evaluated.+-- -   'DataSourceId' - Sets the search criteria to the 'DataSource' used in 'Evaluation'.+-- -   'DataUri' - Sets the search criteria to the data file(s) used in 'Evaluation'. The URL can identify either a file or an Amazon Simple Storage Solution (Amazon S3) bucket or directory. deFilterVariable :: Lens' DescribeEvaluations (Maybe EvaluationFilterVariable) deFilterVariable = lens _deFilterVariable (\ s a -> s{_deFilterVariable = a}); --- | The less than or equal to operator. The 'Evaluation' results will have--- 'FilterVariable' values that are less than or equal to the value--- specified with 'LE'.+-- | The less than or equal to operator. The 'Evaluation' results will have 'FilterVariable' values that are less than or equal to the value specified with 'LE'. deLE :: Lens' DescribeEvaluations (Maybe Text) deLE = lens _deLE (\ s a -> s{_deLE = a}); @@ -255,8 +230,7 @@ instance ToQuery DescribeEvaluations where         toQuery = const mempty --- | Represents the query results from a < DescribeEvaluations> operation.--- The content is essentially a list of 'Evaluation'.+-- | Represents the query results from a < DescribeEvaluations> operation. The content is essentially a list of 'Evaluation'. -- -- /See:/ 'describeEvaluationsResponse' smart constructor. data DescribeEvaluationsResponse = DescribeEvaluationsResponse'@@ -288,8 +262,7 @@ desrsResults :: Lens' DescribeEvaluationsResponse [Evaluation] desrsResults = lens _desrsResults (\ s a -> s{_desrsResults = a}) . _Default . _Coerce; --- | The ID of the next page in the paginated results that indicates at least--- one more page follows.+-- | The ID of the next page in the paginated results that indicates at least one more page follows. desrsNextToken :: Lens' DescribeEvaluationsResponse (Maybe Text) desrsNextToken = lens _desrsNextToken (\ s a -> s{_desrsNextToken = a});
gen/Network/AWS/MachineLearning/DescribeMLModels.hs view
@@ -18,8 +18,7 @@ -- Stability   : auto-generated -- Portability : non-portable (GHC extensions) ----- Returns a list of 'MLModel' that match the search criteria in the--- request.+-- Returns a list of 'MLModel' that match the search criteria in the request. -- -- This operation returns paginated results. module Network.AWS.MachineLearning.DescribeMLModels@@ -114,24 +113,17 @@     , _dmlmLE = Nothing     } --- | The equal to operator. The 'MLModel' results will have 'FilterVariable'--- values that exactly match the value specified with 'EQ'.+-- | The equal to operator. The 'MLModel' results will have 'FilterVariable' values that exactly match the value specified with 'EQ'. dmlmEQ :: Lens' DescribeMLModels (Maybe Text) dmlmEQ = lens _dmlmEQ (\ s a -> s{_dmlmEQ = a}); --- | The greater than or equal to operator. The 'MLModel' results will have--- 'FilterVariable' values that are greater than or equal to the value--- specified with 'GE'.+-- | The greater than or equal to operator. The 'MLModel' results will have 'FilterVariable' values that are greater than or equal to the value specified with 'GE'. dmlmGE :: Lens' DescribeMLModels (Maybe Text) dmlmGE = lens _dmlmGE (\ s a -> s{_dmlmGE = a}); --- | A string that is found at the beginning of a variable, such as 'Name' or--- 'Id'.+-- | A string that is found at the beginning of a variable, such as 'Name' or 'Id'. ----- For example, an 'MLModel' could have the 'Name'--- '2014-09-09-HolidayGiftMailer'. To search for this 'MLModel', select--- 'Name' for the 'FilterVariable' and any of the following strings for the--- 'Prefix':+-- For example, an 'MLModel' could have the 'Name' '2014-09-09-HolidayGiftMailer'. To search for this 'MLModel', select 'Name' for the 'FilterVariable' and any of the following strings for the 'Prefix': -- -- -   2014-09 --@@ -142,14 +134,11 @@ dmlmPrefix :: Lens' DescribeMLModels (Maybe Text) dmlmPrefix = lens _dmlmPrefix (\ s a -> s{_dmlmPrefix = a}); --- | The greater than operator. The 'MLModel' results will have--- 'FilterVariable' values that are greater than the value specified with--- 'GT'.+-- | The greater than operator. The 'MLModel' results will have 'FilterVariable' values that are greater than the value specified with 'GT'. dmlmGT :: Lens' DescribeMLModels (Maybe Text) dmlmGT = lens _dmlmGT (\ s a -> s{_dmlmGT = a}); --- | The not equal to operator. The 'MLModel' results will have--- 'FilterVariable' values not equal to the value specified with 'NE'.+-- | The not equal to operator. The 'MLModel' results will have 'FilterVariable' values not equal to the value specified with 'NE'. dmlmNE :: Lens' DescribeMLModels (Maybe Text) dmlmNE = lens _dmlmNE (\ s a -> s{_dmlmNE = a}); @@ -157,8 +146,7 @@ dmlmNextToken :: Lens' DescribeMLModels (Maybe Text) dmlmNextToken = lens _dmlmNextToken (\ s a -> s{_dmlmNextToken = a}); --- | A two-value parameter that determines the sequence of the resulting list--- of 'MLModel'.+-- | A two-value parameter that determines the sequence of the resulting list of 'MLModel'. -- -- -   'asc' - Arranges the list in ascending order (A-Z, 0-9). -- -   'dsc' - Arranges the list in descending order (Z-A, 9-0).@@ -167,13 +155,11 @@ dmlmSortOrder :: Lens' DescribeMLModels (Maybe SortOrder) dmlmSortOrder = lens _dmlmSortOrder (\ s a -> s{_dmlmSortOrder = a}); --- | The number of pages of information to include in the result. The range--- of acceptable values is 1 through 100. The default value is 100.+-- | The number of pages of information to include in the result. The range of acceptable values is 1 through 100. The default value is 100. dmlmLimit :: Lens' DescribeMLModels (Maybe Natural) dmlmLimit = lens _dmlmLimit (\ s a -> s{_dmlmLimit = a}) . mapping _Nat; --- | The less than operator. The 'MLModel' results will have 'FilterVariable'--- values that are less than the value specified with 'LT'.+-- | The less than operator. The 'MLModel' results will have 'FilterVariable' values that are less than the value specified with 'LT'. dmlmLT :: Lens' DescribeMLModels (Maybe Text) dmlmLT = lens _dmlmLT (\ s a -> s{_dmlmLT = a}); @@ -181,27 +167,17 @@ -- -- -   'CreatedAt' - Sets the search criteria to 'MLModel' creation date. -- -   'Status' - Sets the search criteria to 'MLModel' status.--- -   'Name' - Sets the search criteria to the contents of 'MLModel' ____---     'Name'.--- -   'IAMUser' - Sets the search criteria to the user account that---     invoked the 'MLModel' creation.--- -   'TrainingDataSourceId' - Sets the search criteria to the---     'DataSource' used to train one or more 'MLModel'.--- -   'RealtimeEndpointStatus' - Sets the search criteria to the 'MLModel'---     real-time endpoint status.--- -   'MLModelType' - Sets the search criteria to 'MLModel' type: binary,---     regression, or multi-class.--- -   'Algorithm' - Sets the search criteria to the algorithm that the---     'MLModel' uses.--- -   'TrainingDataURI' - Sets the search criteria to the data file(s)---     used in training a 'MLModel'. The URL can identify either a file or---     an Amazon Simple Storage Service (Amazon S3) bucket or directory.+-- -   'Name' - Sets the search criteria to the contents of 'MLModel' ____ 'Name'.+-- -   'IAMUser' - Sets the search criteria to the user account that invoked the 'MLModel' creation.+-- -   'TrainingDataSourceId' - Sets the search criteria to the 'DataSource' used to train one or more 'MLModel'.+-- -   'RealtimeEndpointStatus' - Sets the search criteria to the 'MLModel' real-time endpoint status.+-- -   'MLModelType' - Sets the search criteria to 'MLModel' type: binary, regression, or multi-class.+-- -   'Algorithm' - Sets the search criteria to the algorithm that the 'MLModel' uses.+-- -   'TrainingDataURI' - Sets the search criteria to the data file(s) used in training a 'MLModel'. The URL can identify either a file or an Amazon Simple Storage Service (Amazon S3) bucket or directory. dmlmFilterVariable :: Lens' DescribeMLModels (Maybe MLModelFilterVariable) dmlmFilterVariable = lens _dmlmFilterVariable (\ s a -> s{_dmlmFilterVariable = a}); --- | The less than or equal to operator. The 'MLModel' results will have--- 'FilterVariable' values that are less than or equal to the value--- specified with 'LE'.+-- | The less than or equal to operator. The 'MLModel' results will have 'FilterVariable' values that are less than or equal to the value specified with 'LE'. dmlmLE :: Lens' DescribeMLModels (Maybe Text) dmlmLE = lens _dmlmLE (\ s a -> s{_dmlmLE = a}); @@ -254,8 +230,7 @@ instance ToQuery DescribeMLModels where         toQuery = const mempty --- | Represents the output of a < DescribeMLModels> operation. The content is--- essentially a list of 'MLModel'.+-- | Represents the output of a < DescribeMLModels> operation. The content is essentially a list of 'MLModel'. -- -- /See:/ 'describeMLModelsResponse' smart constructor. data DescribeMLModelsResponse = DescribeMLModelsResponse'@@ -287,8 +262,7 @@ dmlmsrsResults :: Lens' DescribeMLModelsResponse [MLModel] dmlmsrsResults = lens _dmlmsrsResults (\ s a -> s{_dmlmsrsResults = a}) . _Default . _Coerce; --- | The ID of the next page in the paginated results that indicates at least--- one more page follows.+-- | The ID of the next page in the paginated results that indicates at least one more page follows. dmlmsrsNextToken :: Lens' DescribeMLModelsResponse (Maybe Text) dmlmsrsNextToken = lens _dmlmsrsNextToken (\ s a -> s{_dmlmsrsNextToken = a});
gen/Network/AWS/MachineLearning/GetBatchPrediction.hs view
@@ -18,8 +18,7 @@ -- Stability   : auto-generated -- Portability : non-portable (GHC extensions) ----- Returns a 'BatchPrediction' that includes detailed metadata, status, and--- data file information for a 'Batch Prediction' request.+-- Returns a 'BatchPrediction' that includes detailed metadata, status, and data file information for a 'Batch Prediction' request. module Network.AWS.MachineLearning.GetBatchPrediction     (     -- * Creating a Request@@ -124,8 +123,7 @@ instance ToQuery GetBatchPrediction where         toQuery = const mempty --- | Represents the output of a < GetBatchPrediction> operation and describes--- a 'BatchPrediction'.+-- | Represents the output of a < GetBatchPrediction> operation and describes a 'BatchPrediction'. -- -- /See:/ 'getBatchPredictionResponse' smart constructor. data GetBatchPredictionResponse = GetBatchPredictionResponse'@@ -193,53 +191,41 @@     , _gbprsResponseStatus = pResponseStatus_     } --- | The status of the 'BatchPrediction', which can be one of the following--- values:+-- | The status of the 'BatchPrediction', which can be one of the following values: ----- -   'PENDING' - Amazon Machine Learning (Amazon ML) submitted a request---     to generate batch predictions.+-- -   'PENDING' - Amazon Machine Learning (Amazon ML) submitted a request to generate batch predictions. -- -   'INPROGRESS' - The batch predictions are in progress.--- -   'FAILED' - The request to perform a batch prediction did not run to---     completion. It is not usable.+-- -   'FAILED' - The request to perform a batch prediction did not run to completion. It is not usable. -- -   'COMPLETED' - The batch prediction process completed successfully.--- -   'DELETED' - The 'BatchPrediction' is marked as deleted. It is not---     usable.+-- -   'DELETED' - The 'BatchPrediction' is marked as deleted. It is not usable. gbprsStatus :: Lens' GetBatchPredictionResponse (Maybe EntityStatus) gbprsStatus = lens _gbprsStatus (\ s a -> s{_gbprsStatus = a}); --- | The time of the most recent edit to 'BatchPrediction'. The time is--- expressed in epoch time.+-- | The time of the most recent edit to 'BatchPrediction'. The time is expressed in epoch time. gbprsLastUpdatedAt :: Lens' GetBatchPredictionResponse (Maybe UTCTime) gbprsLastUpdatedAt = lens _gbprsLastUpdatedAt (\ s a -> s{_gbprsLastUpdatedAt = a}) . mapping _Time; --- | The time when the 'BatchPrediction' was created. The time is expressed--- in epoch time.+-- | The time when the 'BatchPrediction' was created. The time is expressed in epoch time. gbprsCreatedAt :: Lens' GetBatchPredictionResponse (Maybe UTCTime) gbprsCreatedAt = lens _gbprsCreatedAt (\ s a -> s{_gbprsCreatedAt = a}) . mapping _Time; --- | The location of the data file or directory in Amazon Simple Storage--- Service (Amazon S3).+-- | The location of the data file or directory in Amazon Simple Storage Service (Amazon S3). gbprsInputDataLocationS3 :: Lens' GetBatchPredictionResponse (Maybe Text) gbprsInputDataLocationS3 = lens _gbprsInputDataLocationS3 (\ s a -> s{_gbprsInputDataLocationS3 = a}); --- | The ID of the 'MLModel' that generated predictions for the--- 'BatchPrediction' request.+-- | The ID of the 'MLModel' that generated predictions for the 'BatchPrediction' request. gbprsMLModelId :: Lens' GetBatchPredictionResponse (Maybe Text) gbprsMLModelId = lens _gbprsMLModelId (\ s a -> s{_gbprsMLModelId = a}); --- | The ID of the 'DataSource' that was used to create the--- 'BatchPrediction'.+-- | The ID of the 'DataSource' that was used to create the 'BatchPrediction'. gbprsBatchPredictionDataSourceId :: Lens' GetBatchPredictionResponse (Maybe Text) gbprsBatchPredictionDataSourceId = lens _gbprsBatchPredictionDataSourceId (\ s a -> s{_gbprsBatchPredictionDataSourceId = a}); --- | An ID assigned to the 'BatchPrediction' at creation. This value should--- be identical to the value of the 'BatchPredictionID' in the request.+-- | An ID assigned to the 'BatchPrediction' at creation. This value should be identical to the value of the 'BatchPredictionID' in the request. gbprsBatchPredictionId :: Lens' GetBatchPredictionResponse (Maybe Text) gbprsBatchPredictionId = lens _gbprsBatchPredictionId (\ s a -> s{_gbprsBatchPredictionId = a}); --- | The AWS user account that invoked the 'BatchPrediction'. The account--- type can be either an AWS root account or an AWS Identity and Access--- Management (IAM) user account.+-- | The AWS user account that invoked the 'BatchPrediction'. The account type can be either an AWS root account or an AWS Identity and Access Management (IAM) user account. gbprsCreatedByIAMUser :: Lens' GetBatchPredictionResponse (Maybe Text) gbprsCreatedByIAMUser = lens _gbprsCreatedByIAMUser (\ s a -> s{_gbprsCreatedByIAMUser = a}); @@ -247,18 +233,15 @@ gbprsName :: Lens' GetBatchPredictionResponse (Maybe Text) gbprsName = lens _gbprsName (\ s a -> s{_gbprsName = a}); --- | A link to the file that contains logs of the < CreateBatchPrediction>--- operation.+-- | A link to the file that contains logs of the < CreateBatchPrediction> operation. gbprsLogURI :: Lens' GetBatchPredictionResponse (Maybe Text) gbprsLogURI = lens _gbprsLogURI (\ s a -> s{_gbprsLogURI = a}); --- | A description of the most recent details about processing the batch--- prediction request.+-- | A description of the most recent details about processing the batch prediction request. gbprsMessage :: Lens' GetBatchPredictionResponse (Maybe Text) gbprsMessage = lens _gbprsMessage (\ s a -> s{_gbprsMessage = a}); --- | The location of an Amazon S3 bucket or directory to receive the--- operation results.+-- | The location of an Amazon S3 bucket or directory to receive the operation results. gbprsOutputURI :: Lens' GetBatchPredictionResponse (Maybe Text) gbprsOutputURI = lens _gbprsOutputURI (\ s a -> s{_gbprsOutputURI = a});
gen/Network/AWS/MachineLearning/GetDataSource.hs view
@@ -18,12 +18,9 @@ -- Stability   : auto-generated -- Portability : non-portable (GHC extensions) ----- Returns a 'DataSource' that includes metadata and data file information,--- as well as the current status of the 'DataSource'.+-- Returns a 'DataSource' that includes metadata and data file information, as well as the current status of the 'DataSource'. ----- 'GetDataSource' provides results in normal or verbose format. The--- verbose format adds the schema description and the list of files pointed--- to by the DataSource to the normal format.+-- 'GetDataSource' provides results in normal or verbose format. The verbose format adds the schema description and the list of files pointed to by the DataSource to the normal format. module Network.AWS.MachineLearning.GetDataSource     (     -- * Creating a Request@@ -86,8 +83,7 @@     , _gdsDataSourceId = pDataSourceId_     } --- | Specifies whether the 'GetDataSource' operation should return--- 'DataSourceSchema'.+-- | Specifies whether the 'GetDataSource' operation should return 'DataSourceSchema'. -- -- If true, 'DataSourceSchema' is returned. --@@ -150,8 +146,7 @@ instance ToQuery GetDataSource where         toQuery = const mempty --- | Represents the output of a < GetDataSource> operation and describes a--- 'DataSource'.+-- | Represents the output of a < GetDataSource> operation and describes a 'DataSource'. -- -- /See:/ 'getDataSourceResponse' smart constructor. data GetDataSourceResponse = GetDataSourceResponse'@@ -239,14 +234,11 @@     , _gdsrsResponseStatus = pResponseStatus_     } --- | The current status of the 'DataSource'. This element can have one of the--- following values:+-- | The current status of the 'DataSource'. This element can have one of the following values: ----- -   'PENDING' - Amazon Machine Language (Amazon ML) submitted a request---     to create a 'DataSource'.+-- -   'PENDING' - Amazon Machine Language (Amazon ML) submitted a request to create a 'DataSource'. -- -   'INPROGRESS' - The creation process is underway.--- -   'FAILED' - The request to create a 'DataSource' did not run to---     completion. It is not usable.+-- -   'FAILED' - The request to create a 'DataSource' did not run to completion. It is not usable. -- -   'COMPLETED' - The creation process completed successfully. -- -   'DELETED' - The 'DataSource' is marked as deleted. It is not usable. gdsrsStatus :: Lens' GetDataSourceResponse (Maybe EntityStatus)@@ -256,18 +248,15 @@ gdsrsNumberOfFiles :: Lens' GetDataSourceResponse (Maybe Integer) gdsrsNumberOfFiles = lens _gdsrsNumberOfFiles (\ s a -> s{_gdsrsNumberOfFiles = a}); --- | The time of the most recent edit to the 'DataSource'. The time is--- expressed in epoch time.+-- | The time of the most recent edit to the 'DataSource'. The time is expressed in epoch time. gdsrsLastUpdatedAt :: Lens' GetDataSourceResponse (Maybe UTCTime) gdsrsLastUpdatedAt = lens _gdsrsLastUpdatedAt (\ s a -> s{_gdsrsLastUpdatedAt = a}) . mapping _Time; --- | The time that the 'DataSource' was created. The time is expressed in--- epoch time.+-- | The time that the 'DataSource' was created. The time is expressed in epoch time. gdsrsCreatedAt :: Lens' GetDataSourceResponse (Maybe UTCTime) gdsrsCreatedAt = lens _gdsrsCreatedAt (\ s a -> s{_gdsrsCreatedAt = a}) . mapping _Time; --- | The ID assigned to the 'DataSource' at creation. This value should be--- identical to the value of the 'DataSourceId' in the request.+-- | The ID assigned to the 'DataSource' at creation. This value should be identical to the value of the 'DataSourceId' in the request. gdsrsDataSourceId :: Lens' GetDataSourceResponse (Maybe Text) gdsrsDataSourceId = lens _gdsrsDataSourceId (\ s a -> s{_gdsrsDataSourceId = a}); @@ -287,9 +276,7 @@ gdsrsDataSourceSchema :: Lens' GetDataSourceResponse (Maybe Text) gdsrsDataSourceSchema = lens _gdsrsDataSourceSchema (\ s a -> s{_gdsrsDataSourceSchema = a}); --- | The AWS user account from which the 'DataSource' was created. The--- account type can be either an AWS root account or an AWS Identity and--- Access Management (IAM) user account.+-- | The AWS user account from which the 'DataSource' was created. The account type can be either an AWS root account or an AWS Identity and Access Management (IAM) user account. gdsrsCreatedByIAMUser :: Lens' GetDataSourceResponse (Maybe Text) gdsrsCreatedByIAMUser = lens _gdsrsCreatedByIAMUser (\ s a -> s{_gdsrsCreatedByIAMUser = a}); @@ -297,23 +284,19 @@ gdsrsName :: Lens' GetDataSourceResponse (Maybe Text) gdsrsName = lens _gdsrsName (\ s a -> s{_gdsrsName = a}); --- | A link to the file containining logs of either create 'DataSource'--- operation.+-- | A link to the file containining logs of either create 'DataSource' operation. gdsrsLogURI :: Lens' GetDataSourceResponse (Maybe Text) gdsrsLogURI = lens _gdsrsLogURI (\ s a -> s{_gdsrsLogURI = a}); --- | The location of the data file or directory in Amazon Simple Storage--- Service (Amazon S3).+-- | The location of the data file or directory in Amazon Simple Storage Service (Amazon S3). gdsrsDataLocationS3 :: Lens' GetDataSourceResponse (Maybe Text) gdsrsDataLocationS3 = lens _gdsrsDataLocationS3 (\ s a -> s{_gdsrsDataLocationS3 = a}); --- | The parameter is 'true' if statistics need to be generated from the--- observation data.+-- | The parameter is 'true' if statistics need to be generated from the observation data. gdsrsComputeStatistics :: Lens' GetDataSourceResponse (Maybe Bool) gdsrsComputeStatistics = lens _gdsrsComputeStatistics (\ s a -> s{_gdsrsComputeStatistics = a}); --- | The description of the most recent details about creating the--- 'DataSource'.+-- | The description of the most recent details about creating the 'DataSource'. gdsrsMessage :: Lens' GetDataSourceResponse (Maybe Text) gdsrsMessage = lens _gdsrsMessage (\ s a -> s{_gdsrsMessage = a}); @@ -321,8 +304,7 @@ gdsrsRedshiftMetadata :: Lens' GetDataSourceResponse (Maybe RedshiftMetadata) gdsrsRedshiftMetadata = lens _gdsrsRedshiftMetadata (\ s a -> s{_gdsrsRedshiftMetadata = a}); --- | A JSON string that captures the splitting rearrangement requirement of--- the 'DataSource'.+-- | A JSON string that captures the splitting rearrangement requirement of the 'DataSource'. gdsrsDataRearrangement :: Lens' GetDataSourceResponse (Maybe Text) gdsrsDataRearrangement = lens _gdsrsDataRearrangement (\ s a -> s{_gdsrsDataRearrangement = a});
gen/Network/AWS/MachineLearning/GetEvaluation.hs view
@@ -18,8 +18,7 @@ -- Stability   : auto-generated -- Portability : non-portable (GHC extensions) ----- Returns an 'Evaluation' that includes metadata as well as the current--- status of the 'Evaluation'.+-- Returns an 'Evaluation' that includes metadata as well as the current status of the 'Evaluation'. module Network.AWS.MachineLearning.GetEvaluation     (     -- * Creating a Request@@ -72,9 +71,7 @@     { _geEvaluationId = pEvaluationId_     } --- | The ID of the 'Evaluation' to retrieve. The evaluation of each 'MLModel'--- is recorded and cataloged. The ID provides the means to access the--- information.+-- | The ID of the 'Evaluation' to retrieve. The evaluation of each 'MLModel' is recorded and cataloged. The ID provides the means to access the information. geEvaluationId :: Lens' GetEvaluation Text geEvaluationId = lens _geEvaluationId (\ s a -> s{_geEvaluationId = a}); @@ -123,8 +120,7 @@ instance ToQuery GetEvaluation where         toQuery = const mempty --- | Represents the output of a < GetEvaluation> operation and describes an--- 'Evaluation'.+-- | Represents the output of a < GetEvaluation> operation and describes an 'Evaluation'. -- -- /See:/ 'getEvaluationResponse' smart constructor. data GetEvaluationResponse = GetEvaluationResponse'@@ -192,51 +188,37 @@     , _gersResponseStatus = pResponseStatus_     } --- | The status of the evaluation. This element can have one of the following--- values:+-- | The status of the evaluation. This element can have one of the following values: ----- -   'PENDING' - Amazon Machine Language (Amazon ML) submitted a request---     to evaluate an 'MLModel'.+-- -   'PENDING' - Amazon Machine Language (Amazon ML) submitted a request to evaluate an 'MLModel'. -- -   'INPROGRESS' - The evaluation is underway.--- -   'FAILED' - The request to evaluate an 'MLModel' did not run to---     completion. It is not usable.+-- -   'FAILED' - The request to evaluate an 'MLModel' did not run to completion. It is not usable. -- -   'COMPLETED' - The evaluation process completed successfully. -- -   'DELETED' - The 'Evaluation' is marked as deleted. It is not usable. gersStatus :: Lens' GetEvaluationResponse (Maybe EntityStatus) gersStatus = lens _gersStatus (\ s a -> s{_gersStatus = a}); --- | Measurements of how well the 'MLModel' performed using observations--- referenced by the 'DataSource'. One of the following metric is returned--- based on the type of the 'MLModel':+-- | Measurements of how well the 'MLModel' performed using observations referenced by the 'DataSource'. One of the following metric is returned based on the type of the 'MLModel': ----- -   BinaryAUC: A binary 'MLModel' uses the Area Under the Curve (AUC)---     technique to measure performance.+-- -   BinaryAUC: A binary 'MLModel' uses the Area Under the Curve (AUC) technique to measure performance. ----- -   RegressionRMSE: A regression 'MLModel' uses the Root Mean Square---     Error (RMSE) technique to measure performance. RMSE measures the---     difference between predicted and actual values for a single---     variable.+-- -   RegressionRMSE: A regression 'MLModel' uses the Root Mean Square Error (RMSE) technique to measure performance. RMSE measures the difference between predicted and actual values for a single variable. ----- -   MulticlassAvgFScore: A multiclass 'MLModel' uses the F1 score---     technique to measure performance.+-- -   MulticlassAvgFScore: A multiclass 'MLModel' uses the F1 score technique to measure performance. ----- For more information about performance metrics, please see the--- <http://docs.aws.amazon.com/machine-learning/latest/dg Amazon Machine Learning Developer Guide>.+-- For more information about performance metrics, please see the <http://docs.aws.amazon.com/machine-learning/latest/dg Amazon Machine Learning Developer Guide>. gersPerformanceMetrics :: Lens' GetEvaluationResponse (Maybe PerformanceMetrics) gersPerformanceMetrics = lens _gersPerformanceMetrics (\ s a -> s{_gersPerformanceMetrics = a}); --- | The time of the most recent edit to the 'BatchPrediction'. The time is--- expressed in epoch time.+-- | The time of the most recent edit to the 'BatchPrediction'. The time is expressed in epoch time. gersLastUpdatedAt :: Lens' GetEvaluationResponse (Maybe UTCTime) gersLastUpdatedAt = lens _gersLastUpdatedAt (\ s a -> s{_gersLastUpdatedAt = a}) . mapping _Time; --- | The time that the 'Evaluation' was created. The time is expressed in--- epoch time.+-- | The time that the 'Evaluation' was created. The time is expressed in epoch time. gersCreatedAt :: Lens' GetEvaluationResponse (Maybe UTCTime) gersCreatedAt = lens _gersCreatedAt (\ s a -> s{_gersCreatedAt = a}) . mapping _Time; --- | The location of the data file or directory in Amazon Simple Storage--- Service (Amazon S3).+-- | The location of the data file or directory in Amazon Simple Storage Service (Amazon S3). gersInputDataLocationS3 :: Lens' GetEvaluationResponse (Maybe Text) gersInputDataLocationS3 = lens _gersInputDataLocationS3 (\ s a -> s{_gersInputDataLocationS3 = a}); @@ -244,9 +226,7 @@ gersMLModelId :: Lens' GetEvaluationResponse (Maybe Text) gersMLModelId = lens _gersMLModelId (\ s a -> s{_gersMLModelId = a}); --- | The AWS user account that invoked the evaluation. The account type can--- be either an AWS root account or an AWS Identity and Access Management--- (IAM) user account.+-- | The AWS user account that invoked the evaluation. The account type can be either an AWS root account or an AWS Identity and Access Management (IAM) user account. gersCreatedByIAMUser :: Lens' GetEvaluationResponse (Maybe Text) gersCreatedByIAMUser = lens _gersCreatedByIAMUser (\ s a -> s{_gersCreatedByIAMUser = a}); @@ -254,8 +234,7 @@ gersName :: Lens' GetEvaluationResponse (Maybe Text) gersName = lens _gersName (\ s a -> s{_gersName = a}); --- | A link to the file that contains logs of the < CreateEvaluation>--- operation.+-- | A link to the file that contains logs of the < CreateEvaluation> operation. gersLogURI :: Lens' GetEvaluationResponse (Maybe Text) gersLogURI = lens _gersLogURI (\ s a -> s{_gersLogURI = a});
gen/Network/AWS/MachineLearning/GetMLModel.hs view
@@ -18,8 +18,7 @@ -- Stability   : auto-generated -- Portability : non-portable (GHC extensions) ----- Returns an 'MLModel' that includes detailed metadata, and data source--- information as well as the current status of the 'MLModel'.+-- Returns an 'MLModel' that includes detailed metadata, and data source information as well as the current status of the 'MLModel'. -- -- 'GetMLModel' provides results in normal or verbose format. module Network.AWS.MachineLearning.GetMLModel@@ -149,8 +148,7 @@ instance ToQuery GetMLModel where         toQuery = const mempty --- | Represents the output of a < GetMLModel> operation, and provides--- detailed information about a 'MLModel'.+-- | Represents the output of a < GetMLModel> operation, and provides detailed information about a 'MLModel'. -- -- /See:/ 'getMLModelResponse' smart constructor. data GetMLModelResponse = GetMLModelResponse'@@ -242,11 +240,9 @@     , _gmlmrsResponseStatus = pResponseStatus_     } --- | The current status of the 'MLModel'. This element can have one of the--- following values:+-- | The current status of the 'MLModel'. This element can have one of the following values: ----- -   'PENDING' - Amazon Machine Learning (Amazon ML) submitted a request---     to describe a 'MLModel'.+-- -   'PENDING' - Amazon Machine Learning (Amazon ML) submitted a request to describe a 'MLModel'. -- -   'INPROGRESS' - The request is processing. -- -   'FAILED' - The request did not run to completion. It is not usable. -- -   'COMPLETED' - The request completed successfully.@@ -254,64 +250,40 @@ gmlmrsStatus :: Lens' GetMLModelResponse (Maybe EntityStatus) gmlmrsStatus = lens _gmlmrsStatus (\ s a -> s{_gmlmrsStatus = a}); --- | The time of the most recent edit to the 'MLModel'. The time is expressed--- in epoch time.+-- | The time of the most recent edit to the 'MLModel'. The time is expressed in epoch time. gmlmrsLastUpdatedAt :: Lens' GetMLModelResponse (Maybe UTCTime) gmlmrsLastUpdatedAt = lens _gmlmrsLastUpdatedAt (\ s a -> s{_gmlmrsLastUpdatedAt = a}) . mapping _Time; --- | A list of the training parameters in the 'MLModel'. The list is--- implemented as a map of key\/value pairs.+-- | A list of the training parameters in the 'MLModel'. The list is implemented as a map of key\/value pairs. -- -- The following is the current set of training parameters: ----- -   'sgd.l1RegularizationAmount' - Coefficient regularization L1 norm.---     It controls overfitting the data by penalizing large coefficients.---     This tends to drive coefficients to zero, resulting in a sparse---     feature set. If you use this parameter, specify a small value, such---     as 1.0E-04 or 1.0E-08.+-- -   'sgd.l1RegularizationAmount' - Coefficient regularization L1 norm. It controls overfitting the data by penalizing large coefficients. This tends to drive coefficients to zero, resulting in a sparse feature set. If you use this parameter, specify a small value, such as 1.0E-04 or 1.0E-08. -----     The value is a double that ranges from 0 to MAX_DOUBLE. The default---     is not to use L1 normalization. The parameter cannot be used when---     'L2' is specified. Use this parameter sparingly.+--     The value is a double that ranges from 0 to MAX_DOUBLE. The default is not to use L1 normalization. The parameter cannot be used when 'L2' is specified. Use this parameter sparingly. ----- -   'sgd.l2RegularizationAmount' - Coefficient regularization L2 norm.---     It controls overfitting the data by penalizing large coefficients.---     This tends to drive coefficients to small, nonzero values. If you---     use this parameter, specify a small value, such as 1.0E-04 or---     1.0E-08.+-- -   'sgd.l2RegularizationAmount' - Coefficient regularization L2 norm. It controls overfitting the data by penalizing large coefficients. This tends to drive coefficients to small, nonzero values. If you use this parameter, specify a small value, such as 1.0E-04 or 1.0E-08. -----     The value is a double that ranges from 0 to MAX_DOUBLE. The default---     is not to use L2 normalization. This parameter cannot be used when---     'L1' is specified. Use this parameter sparingly.+--     The value is a double that ranges from 0 to MAX_DOUBLE. The default is not to use L2 normalization. This parameter cannot be used when 'L1' is specified. Use this parameter sparingly. ----- -   'sgd.maxPasses' - The number of times that the training process---     traverses the observations to build the 'MLModel'. The value is an---     integer that ranges from 1 to 10000. The default value is 10.+-- -   'sgd.maxPasses' - The number of times that the training process traverses the observations to build the 'MLModel'. The value is an integer that ranges from 1 to 10000. The default value is 10. ----- -   'sgd.maxMLModelSizeInBytes' - The maximum allowed size of the model.---     Depending on the input data, the model size might affect---     performance.+-- -   'sgd.maxMLModelSizeInBytes' - The maximum allowed size of the model. Depending on the input data, the model size might affect performance. -----     The value is an integer that ranges from 100000 to 2147483648. The---     default value is 33554432.+--     The value is an integer that ranges from 100000 to 2147483648. The default value is 33554432. -- gmlmrsTrainingParameters :: Lens' GetMLModelResponse (HashMap Text Text) gmlmrsTrainingParameters = lens _gmlmrsTrainingParameters (\ s a -> s{_gmlmrsTrainingParameters = a}) . _Default . _Map; --- | The time of the most recent edit to the 'ScoreThreshold'. The time is--- expressed in epoch time.+-- | The time of the most recent edit to the 'ScoreThreshold'. The time is expressed in epoch time. gmlmrsScoreThresholdLastUpdatedAt :: Lens' GetMLModelResponse (Maybe UTCTime) gmlmrsScoreThresholdLastUpdatedAt = lens _gmlmrsScoreThresholdLastUpdatedAt (\ s a -> s{_gmlmrsScoreThresholdLastUpdatedAt = a}) . mapping _Time; --- | The time that the 'MLModel' was created. The time is expressed in epoch--- time.+-- | The time that the 'MLModel' was created. The time is expressed in epoch time. gmlmrsCreatedAt :: Lens' GetMLModelResponse (Maybe UTCTime) gmlmrsCreatedAt = lens _gmlmrsCreatedAt (\ s a -> s{_gmlmrsCreatedAt = a}) . mapping _Time; --- | The recipe to use when training the 'MLModel'. The 'Recipe' provides--- detailed information about the observation data to use during training,--- as well as manipulations to perform on the observation data during--- training.+-- | The recipe to use when training the 'MLModel'. The 'Recipe' provides detailed information about the observation data to use during training, as well as manipulations to perform on the observation data during training. -- -- Note --@@ -319,8 +291,7 @@ gmlmrsRecipe :: Lens' GetMLModelResponse (Maybe Text) gmlmrsRecipe = lens _gmlmrsRecipe (\ s a -> s{_gmlmrsRecipe = a}); --- | The location of the data file or directory in Amazon Simple Storage--- Service (Amazon S3).+-- | The location of the data file or directory in Amazon Simple Storage Service (Amazon S3). gmlmrsInputDataLocationS3 :: Lens' GetMLModelResponse (Maybe Text) gmlmrsInputDataLocationS3 = lens _gmlmrsInputDataLocationS3 (\ s a -> s{_gmlmrsInputDataLocationS3 = a}); @@ -340,19 +311,13 @@ gmlmrsSchema :: Lens' GetMLModelResponse (Maybe Text) gmlmrsSchema = lens _gmlmrsSchema (\ s a -> s{_gmlmrsSchema = a}); --- | The scoring threshold is used in binary classification 'MLModel's, and--- marks the boundary between a positive prediction and a negative--- prediction.+-- | The scoring threshold is used in binary classification 'MLModel's, and marks the boundary between a positive prediction and a negative prediction. ----- Output values greater than or equal to the threshold receive a positive--- result from the MLModel, such as 'true'. Output values less than the--- threshold receive a negative response from the MLModel, such as 'false'.+-- Output values greater than or equal to the threshold receive a positive result from the MLModel, such as 'true'. Output values less than the threshold receive a negative response from the MLModel, such as 'false'. gmlmrsScoreThreshold :: Lens' GetMLModelResponse (Maybe Double) gmlmrsScoreThreshold = lens _gmlmrsScoreThreshold (\ s a -> s{_gmlmrsScoreThreshold = a}); --- | The AWS user account from which the 'MLModel' was created. The account--- type can be either an AWS root account or an AWS Identity and Access--- Management (IAM) user account.+-- | The AWS user account from which the 'MLModel' was created. The account type can be either an AWS root account or an AWS Identity and Access Management (IAM) user account. gmlmrsCreatedByIAMUser :: Lens' GetMLModelResponse (Maybe Text) gmlmrsCreatedByIAMUser = lens _gmlmrsCreatedByIAMUser (\ s a -> s{_gmlmrsCreatedByIAMUser = a}); @@ -376,15 +341,11 @@ gmlmrsMessage :: Lens' GetMLModelResponse (Maybe Text) gmlmrsMessage = lens _gmlmrsMessage (\ s a -> s{_gmlmrsMessage = a}); --- | Identifies the 'MLModel' category. The following are the available--- types:+-- | Identifies the 'MLModel' category. The following are the available types: ----- -   REGRESSION -- Produces a numeric result. For example, \"What listing---     price should a house have?\"--- -   BINARY -- Produces one of two possible results. For example, \"Is---     this an e-commerce website?\"--- -   MULTICLASS -- Produces more than two possible results. For example,---     \"Is this a HIGH, LOW or MEDIUM risk trade?\"+-- -   REGRESSION -- Produces a numeric result. For example, \"What listing price should a house have?\"+-- -   BINARY -- Produces one of two possible results. For example, \"Is this an e-commerce website?\"+-- -   MULTICLASS -- Produces more than two possible results. For example, \"Is this a HIGH, LOW or MEDIUM risk trade?\" gmlmrsMLModelType :: Lens' GetMLModelResponse (Maybe MLModelType) gmlmrsMLModelType = lens _gmlmrsMLModelType (\ s a -> s{_gmlmrsMLModelType = a});
gen/Network/AWS/MachineLearning/Predict.hs view
@@ -18,13 +18,11 @@ -- Stability   : auto-generated -- Portability : non-portable (GHC extensions) ----- Generates a prediction for the observation using the specified--- 'ML Model'.+-- Generates a prediction for the observation using the specified 'ML Model'. -- -- Note ----- Not all response parameters will be populated. Whether a response--- parameter is populated depends on the type of model requested.+-- Not all response parameters will be populated. Whether a response parameter is populated depends on the type of model requested. module Network.AWS.MachineLearning.Predict     (     -- * Creating a Request
gen/Network/AWS/MachineLearning/Types.hs view
@@ -264,22 +264,18 @@ _InternalServerException =     _ServiceError . hasStatus 500 . hasCode "InternalServerException" --- | An error on the client occurred. Typically, the cause is an invalid--- input value.+-- | An error on the client occurred. Typically, the cause is an invalid input value. _InvalidInputException :: AsError a => Getting (First ServiceError) a ServiceError _InvalidInputException =     _ServiceError . hasStatus 400 . hasCode "InvalidInputException" --- | A second request to use or change an object was not allowed. This can--- result from retrying a request using a parameter that was not present in--- the original request.+-- | A second request to use or change an object was not allowed. This can result from retrying a request using a parameter that was not present in the original request. _IdempotentParameterMismatchException :: AsError a => Getting (First ServiceError) a ServiceError _IdempotentParameterMismatchException =     _ServiceError .     hasStatus 400 . hasCode "IdempotentParameterMismatchException" --- | The exception is thrown when a predict request is made to an unmounted--- 'MLModel'.+-- | The exception is thrown when a predict request is made to an unmounted 'MLModel'. _PredictorNotMountedException :: AsError a => Getting (First ServiceError) a ServiceError _PredictorNotMountedException =     _ServiceError . hasStatus 400 . hasCode "PredictorNotMountedException"@@ -289,8 +285,7 @@ _ResourceNotFoundException =     _ServiceError . hasStatus 404 . hasCode "ResourceNotFoundException" --- | The subscriber exceeded the maximum number of operations. This exception--- can occur when listing objects such as 'DataSource'.+-- | The subscriber exceeded the maximum number of operations. This exception can occur when listing objects such as 'DataSource'. _LimitExceededException :: AsError a => Getting (First ServiceError) a ServiceError _LimitExceededException =     _ServiceError . hasStatus 417 . hasCode "LimitExceededException"
gen/Network/AWS/MachineLearning/Types/Product.hs view
@@ -23,8 +23,7 @@  -- | Represents the output of < GetBatchPrediction> operation. ----- The content consists of the detailed metadata, the status, and the data--- file information of a /Batch Prediction/.+-- The content consists of the detailed metadata, the status, and the data file information of a /Batch Prediction/. -- -- /See:/ 'batchPrediction' smart constructor. data BatchPrediction = BatchPrediction'@@ -83,53 +82,41 @@     , _bpOutputURI = Nothing     } --- | The status of the 'BatchPrediction'. This element can have one of the--- following values:+-- | The status of the 'BatchPrediction'. This element can have one of the following values: ----- -   'PENDING' - Amazon Machine Learning (Amazon ML) submitted a request---     to generate predictions for a batch of observations.+-- -   'PENDING' - Amazon Machine Learning (Amazon ML) submitted a request to generate predictions for a batch of observations. -- -   'INPROGRESS' - The process is underway.--- -   'FAILED' - The request to peform a batch prediction did not run to---     completion. It is not usable.+-- -   'FAILED' - The request to peform a batch prediction did not run to completion. It is not usable. -- -   'COMPLETED' - The batch prediction process completed successfully.--- -   'DELETED' - The 'BatchPrediction' is marked as deleted. It is not---     usable.+-- -   'DELETED' - The 'BatchPrediction' is marked as deleted. It is not usable. bpStatus :: Lens' BatchPrediction (Maybe EntityStatus) bpStatus = lens _bpStatus (\ s a -> s{_bpStatus = a}); --- | The time of the most recent edit to the 'BatchPrediction'. The time is--- expressed in epoch time.+-- | The time of the most recent edit to the 'BatchPrediction'. The time is expressed in epoch time. bpLastUpdatedAt :: Lens' BatchPrediction (Maybe UTCTime) bpLastUpdatedAt = lens _bpLastUpdatedAt (\ s a -> s{_bpLastUpdatedAt = a}) . mapping _Time; --- | The time that the 'BatchPrediction' was created. The time is expressed--- in epoch time.+-- | The time that the 'BatchPrediction' was created. The time is expressed in epoch time. bpCreatedAt :: Lens' BatchPrediction (Maybe UTCTime) bpCreatedAt = lens _bpCreatedAt (\ s a -> s{_bpCreatedAt = a}) . mapping _Time; --- | The location of the data file or directory in Amazon Simple Storage--- Service (Amazon S3).+-- | The location of the data file or directory in Amazon Simple Storage Service (Amazon S3). bpInputDataLocationS3 :: Lens' BatchPrediction (Maybe Text) bpInputDataLocationS3 = lens _bpInputDataLocationS3 (\ s a -> s{_bpInputDataLocationS3 = a}); --- | The ID of the 'MLModel' that generated predictions for the--- 'BatchPrediction' request.+-- | The ID of the 'MLModel' that generated predictions for the 'BatchPrediction' request. bpMLModelId :: Lens' BatchPrediction (Maybe Text) bpMLModelId = lens _bpMLModelId (\ s a -> s{_bpMLModelId = a}); --- | The ID of the 'DataSource' that points to the group of observations to--- predict.+-- | The ID of the 'DataSource' that points to the group of observations to predict. bpBatchPredictionDataSourceId :: Lens' BatchPrediction (Maybe Text) bpBatchPredictionDataSourceId = lens _bpBatchPredictionDataSourceId (\ s a -> s{_bpBatchPredictionDataSourceId = a}); --- | The ID assigned to the 'BatchPrediction' at creation. This value should--- be identical to the value of the 'BatchPredictionID' in the request.+-- | The ID assigned to the 'BatchPrediction' at creation. This value should be identical to the value of the 'BatchPredictionID' in the request. bpBatchPredictionId :: Lens' BatchPrediction (Maybe Text) bpBatchPredictionId = lens _bpBatchPredictionId (\ s a -> s{_bpBatchPredictionId = a}); --- | The AWS user account that invoked the 'BatchPrediction'. The account--- type can be either an AWS root account or an AWS Identity and Access--- Management (IAM) user account.+-- | The AWS user account that invoked the 'BatchPrediction'. The account type can be either an AWS root account or an AWS Identity and Access Management (IAM) user account. bpCreatedByIAMUser :: Lens' BatchPrediction (Maybe Text) bpCreatedByIAMUser = lens _bpCreatedByIAMUser (\ s a -> s{_bpCreatedByIAMUser = a}); @@ -137,15 +124,11 @@ bpName :: Lens' BatchPrediction (Maybe Text) bpName = lens _bpName (\ s a -> s{_bpName = a}); --- | A description of the most recent details about processing the batch--- prediction request.+-- | A description of the most recent details about processing the batch prediction request. bpMessage :: Lens' BatchPrediction (Maybe Text) bpMessage = lens _bpMessage (\ s a -> s{_bpMessage = a}); --- | The location of an Amazon S3 bucket or directory to receive the--- operation results. The following substrings are not allowed in the s3--- key portion of the \"outputURI\" field: \':\', \'\/\/\', \'\/.\/\',--- \'\/..\/\'.+-- | The location of an Amazon S3 bucket or directory to receive the operation results. The following substrings are not allowed in the s3 key portion of the \"outputURI\" field: \':\', \'\/\/\', \'\/.\/\', \'\/..\/\'. bpOutputURI :: Lens' BatchPrediction (Maybe Text) bpOutputURI = lens _bpOutputURI (\ s a -> s{_bpOutputURI = a}); @@ -171,8 +154,7 @@  -- | Represents the output of the < GetDataSource> operation. ----- The content consists of the detailed metadata and data file information--- and the current status of the 'DataSource'.+-- The content consists of the detailed metadata and data file information and the current status of the 'DataSource'. -- -- /See:/ 'dataSource' smart constructor. data DataSource = DataSource'@@ -247,14 +229,11 @@     , _dsRoleARN = Nothing     } --- | The current status of the 'DataSource'. This element can have one of the--- following values:+-- | The current status of the 'DataSource'. This element can have one of the following values: ----- -   PENDING - Amazon Machine Learning (Amazon ML) submitted a request to---     create a 'DataSource'.+-- -   PENDING - Amazon Machine Learning (Amazon ML) submitted a request to create a 'DataSource'. -- -   INPROGRESS - The creation process is underway.--- -   FAILED - The request to create a 'DataSource' did not run to---     completion. It is not usable.+-- -   FAILED - The request to create a 'DataSource' did not run to completion. It is not usable. -- -   COMPLETED - The creation process completed successfully. -- -   DELETED - The 'DataSource' is marked as deleted. It is not usable. dsStatus :: Lens' DataSource (Maybe EntityStatus)@@ -264,13 +243,11 @@ dsNumberOfFiles :: Lens' DataSource (Maybe Integer) dsNumberOfFiles = lens _dsNumberOfFiles (\ s a -> s{_dsNumberOfFiles = a}); --- | The time of the most recent edit to the 'BatchPrediction'. The time is--- expressed in epoch time.+-- | The time of the most recent edit to the 'BatchPrediction'. The time is expressed in epoch time. dsLastUpdatedAt :: Lens' DataSource (Maybe UTCTime) dsLastUpdatedAt = lens _dsLastUpdatedAt (\ s a -> s{_dsLastUpdatedAt = a}) . mapping _Time; --- | The time that the 'DataSource' was created. The time is expressed in--- epoch time.+-- | The time that the 'DataSource' was created. The time is expressed in epoch time. dsCreatedAt :: Lens' DataSource (Maybe UTCTime) dsCreatedAt = lens _dsCreatedAt (\ s a -> s{_dsCreatedAt = a}) . mapping _Time; @@ -282,14 +259,11 @@ dsRDSMetadata :: Lens' DataSource (Maybe RDSMetadata) dsRDSMetadata = lens _dsRDSMetadata (\ s a -> s{_dsRDSMetadata = a}); --- | The total number of observations contained in the data files that the--- 'DataSource' references.+-- | The total number of observations contained in the data files that the 'DataSource' references. dsDataSizeInBytes :: Lens' DataSource (Maybe Integer) dsDataSizeInBytes = lens _dsDataSizeInBytes (\ s a -> s{_dsDataSizeInBytes = a}); --- | The AWS user account from which the 'DataSource' was created. The--- account type can be either an AWS root account or an AWS Identity and--- Access Management (IAM) user account.+-- | The AWS user account from which the 'DataSource' was created. The account type can be either an AWS root account or an AWS Identity and Access Management (IAM) user account. dsCreatedByIAMUser :: Lens' DataSource (Maybe Text) dsCreatedByIAMUser = lens _dsCreatedByIAMUser (\ s a -> s{_dsCreatedByIAMUser = a}); @@ -297,18 +271,15 @@ dsName :: Lens' DataSource (Maybe Text) dsName = lens _dsName (\ s a -> s{_dsName = a}); --- | The location and name of the data in Amazon Simple Storage Service--- (Amazon S3) that is used by a 'DataSource'.+-- | The location and name of the data in Amazon Simple Storage Service (Amazon S3) that is used by a 'DataSource'. dsDataLocationS3 :: Lens' DataSource (Maybe Text) dsDataLocationS3 = lens _dsDataLocationS3 (\ s a -> s{_dsDataLocationS3 = a}); --- | The parameter is 'true' if statistics need to be generated from the--- observation data.+-- | The parameter is 'true' if statistics need to be generated from the observation data. dsComputeStatistics :: Lens' DataSource (Maybe Bool) dsComputeStatistics = lens _dsComputeStatistics (\ s a -> s{_dsComputeStatistics = a}); --- | A description of the most recent details about creating the--- 'DataSource'.+-- | A description of the most recent details about creating the 'DataSource'. dsMessage :: Lens' DataSource (Maybe Text) dsMessage = lens _dsMessage (\ s a -> s{_dsMessage = a}); @@ -316,8 +287,7 @@ dsRedshiftMetadata :: Lens' DataSource (Maybe RedshiftMetadata) dsRedshiftMetadata = lens _dsRedshiftMetadata (\ s a -> s{_dsRedshiftMetadata = a}); --- | A JSON string that represents the splitting requirement of a--- 'Datasource'.+-- | A JSON string that represents the splitting requirement of a 'Datasource'. dsDataRearrangement :: Lens' DataSource (Maybe Text) dsDataRearrangement = lens _dsDataRearrangement (\ s a -> s{_dsDataRearrangement = a}); @@ -351,8 +321,7 @@  -- | Represents the output of < GetEvaluation> operation. ----- The content consists of the detailed metadata and data file information--- and the current status of the 'Evaluation'.+-- The content consists of the detailed metadata and data file information and the current status of the 'Evaluation'. -- -- /See:/ 'evaluation' smart constructor. data Evaluation = Evaluation'@@ -411,51 +380,37 @@     , _eEvaluationDataSourceId = Nothing     } --- | The status of the evaluation. This element can have one of the following--- values:+-- | The status of the evaluation. This element can have one of the following values: ----- -   'PENDING' - Amazon Machine Learning (Amazon ML) submitted a request---     to evaluate an 'MLModel'.+-- -   'PENDING' - Amazon Machine Learning (Amazon ML) submitted a request to evaluate an 'MLModel'. -- -   'INPROGRESS' - The evaluation is underway.--- -   'FAILED' - The request to evaluate an 'MLModel' did not run to---     completion. It is not usable.+-- -   'FAILED' - The request to evaluate an 'MLModel' did not run to completion. It is not usable. -- -   'COMPLETED' - The evaluation process completed successfully. -- -   'DELETED' - The 'Evaluation' is marked as deleted. It is not usable. eStatus :: Lens' Evaluation (Maybe EntityStatus) eStatus = lens _eStatus (\ s a -> s{_eStatus = a}); --- | Measurements of how well the 'MLModel' performed, using observations--- referenced by the 'DataSource'. One of the following metrics is--- returned, based on the type of the MLModel:+-- | Measurements of how well the 'MLModel' performed, using observations referenced by the 'DataSource'. One of the following metrics is returned, based on the type of the MLModel: ----- -   BinaryAUC: A binary 'MLModel' uses the Area Under the Curve (AUC)---     technique to measure performance.+-- -   BinaryAUC: A binary 'MLModel' uses the Area Under the Curve (AUC) technique to measure performance. ----- -   RegressionRMSE: A regression 'MLModel' uses the Root Mean Square---     Error (RMSE) technique to measure performance. RMSE measures the---     difference between predicted and actual values for a single---     variable.+-- -   RegressionRMSE: A regression 'MLModel' uses the Root Mean Square Error (RMSE) technique to measure performance. RMSE measures the difference between predicted and actual values for a single variable. ----- -   MulticlassAvgFScore: A multiclass 'MLModel' uses the F1 score---     technique to measure performance.+-- -   MulticlassAvgFScore: A multiclass 'MLModel' uses the F1 score technique to measure performance. ----- For more information about performance metrics, please see the--- <http://docs.aws.amazon.com/machine-learning/latest/dg Amazon Machine Learning Developer Guide>.+-- For more information about performance metrics, please see the <http://docs.aws.amazon.com/machine-learning/latest/dg Amazon Machine Learning Developer Guide>. ePerformanceMetrics :: Lens' Evaluation (Maybe PerformanceMetrics) ePerformanceMetrics = lens _ePerformanceMetrics (\ s a -> s{_ePerformanceMetrics = a}); --- | The time of the most recent edit to the 'Evaluation'. The time is--- expressed in epoch time.+-- | The time of the most recent edit to the 'Evaluation'. The time is expressed in epoch time. eLastUpdatedAt :: Lens' Evaluation (Maybe UTCTime) eLastUpdatedAt = lens _eLastUpdatedAt (\ s a -> s{_eLastUpdatedAt = a}) . mapping _Time; --- | The time that the 'Evaluation' was created. The time is expressed in--- epoch time.+-- | The time that the 'Evaluation' was created. The time is expressed in epoch time. eCreatedAt :: Lens' Evaluation (Maybe UTCTime) eCreatedAt = lens _eCreatedAt (\ s a -> s{_eCreatedAt = a}) . mapping _Time; --- | The location and name of the data in Amazon Simple Storage Server--- (Amazon S3) that is used in the evaluation.+-- | The location and name of the data in Amazon Simple Storage Server (Amazon S3) that is used in the evaluation. eInputDataLocationS3 :: Lens' Evaluation (Maybe Text) eInputDataLocationS3 = lens _eInputDataLocationS3 (\ s a -> s{_eInputDataLocationS3 = a}); @@ -463,9 +418,7 @@ eMLModelId :: Lens' Evaluation (Maybe Text) eMLModelId = lens _eMLModelId (\ s a -> s{_eMLModelId = a}); --- | The AWS user account that invoked the evaluation. The account type can--- be either an AWS root account or an AWS Identity and Access Management--- (IAM) user account.+-- | The AWS user account that invoked the evaluation. The account type can be either an AWS root account or an AWS Identity and Access Management (IAM) user account. eCreatedByIAMUser :: Lens' Evaluation (Maybe Text) eCreatedByIAMUser = lens _eCreatedByIAMUser (\ s a -> s{_eCreatedByIAMUser = a}); @@ -507,8 +460,7 @@  -- | Represents the output of a < GetMLModel> operation. ----- The content consists of the detailed metadata and the current status of--- the 'MLModel'.+-- The content consists of the detailed metadata and the current status of the 'MLModel'. -- -- /See:/ 'mLModel' smart constructor. data MLModel = MLModel'@@ -587,75 +539,50 @@     , _mlmMLModelType = Nothing     } --- | The current status of an 'MLModel'. This element can have one of the--- following values:+-- | The current status of an 'MLModel'. This element can have one of the following values: ----- -   PENDING - Amazon Machine Learning (Amazon ML) submitted a request to---     create an 'MLModel'.+-- -   PENDING - Amazon Machine Learning (Amazon ML) submitted a request to create an 'MLModel'. -- -   INPROGRESS - The creation process is underway.--- -   FAILED - The request to create an 'MLModel' did not run to---     completion. It is not usable.+-- -   FAILED - The request to create an 'MLModel' did not run to completion. It is not usable. -- -   COMPLETED - The creation process completed successfully. -- -   DELETED - The 'MLModel' is marked as deleted. It is not usable. mlmStatus :: Lens' MLModel (Maybe EntityStatus) mlmStatus = lens _mlmStatus (\ s a -> s{_mlmStatus = a}); --- | The time of the most recent edit to the 'MLModel'. The time is expressed--- in epoch time.+-- | The time of the most recent edit to the 'MLModel'. The time is expressed in epoch time. mlmLastUpdatedAt :: Lens' MLModel (Maybe UTCTime) mlmLastUpdatedAt = lens _mlmLastUpdatedAt (\ s a -> s{_mlmLastUpdatedAt = a}) . mapping _Time; --- | A list of the training parameters in the 'MLModel'. The list is--- implemented as a map of key\/value pairs.+-- | A list of the training parameters in the 'MLModel'. The list is implemented as a map of key\/value pairs. -- -- The following is the current set of training parameters: ----- -   'sgd.l1RegularizationAmount' - Coefficient regularization L1 norm.---     It controls overfitting the data by penalizing large coefficients.---     This tends to drive coefficients to zero, resulting in a sparse---     feature set. If you use this parameter, specify a small value, such---     as 1.0E-04 or 1.0E-08.+-- -   'sgd.l1RegularizationAmount' - Coefficient regularization L1 norm. It controls overfitting the data by penalizing large coefficients. This tends to drive coefficients to zero, resulting in a sparse feature set. If you use this parameter, specify a small value, such as 1.0E-04 or 1.0E-08. -----     The value is a double that ranges from 0 to MAX_DOUBLE. The default---     is not to use L1 normalization. The parameter cannot be used when---     'L2' is specified. Use this parameter sparingly.+--     The value is a double that ranges from 0 to MAX_DOUBLE. The default is not to use L1 normalization. The parameter cannot be used when 'L2' is specified. Use this parameter sparingly. ----- -   'sgd.l2RegularizationAmount' - Coefficient regularization L2 norm.---     It controls overfitting the data by penalizing large coefficients.---     This tends to drive coefficients to small, nonzero values. If you---     use this parameter, specify a small value, such as 1.0E-04 or---     1.0E-08.+-- -   'sgd.l2RegularizationAmount' - Coefficient regularization L2 norm. It controls overfitting the data by penalizing large coefficients. This tends to drive coefficients to small, nonzero values. If you use this parameter, specify a small value, such as 1.0E-04 or 1.0E-08. -----     The valus is a double that ranges from 0 to MAX_DOUBLE. The default---     is not to use L2 normalization. This cannot be used when 'L1' is---     specified. Use this parameter sparingly.+--     The valus is a double that ranges from 0 to MAX_DOUBLE. The default is not to use L2 normalization. This cannot be used when 'L1' is specified. Use this parameter sparingly. ----- -   'sgd.maxPasses' - Number of times that the training process---     traverses the observations to build the 'MLModel'. The value is an---     integer that ranges from 1 to 10000. The default value is 10.+-- -   'sgd.maxPasses' - Number of times that the training process traverses the observations to build the 'MLModel'. The value is an integer that ranges from 1 to 10000. The default value is 10. ----- -   'sgd.maxMLModelSizeInBytes' - Maximum allowed size of the model.---     Depending on the input data, the model size might affect---     performance.+-- -   'sgd.maxMLModelSizeInBytes' - Maximum allowed size of the model. Depending on the input data, the model size might affect performance. -----     The value is an integer that ranges from 100000 to 2147483648. The---     default value is 33554432.+--     The value is an integer that ranges from 100000 to 2147483648. The default value is 33554432. -- mlmTrainingParameters :: Lens' MLModel (HashMap Text Text) mlmTrainingParameters = lens _mlmTrainingParameters (\ s a -> s{_mlmTrainingParameters = a}) . _Default . _Map; --- | The time of the most recent edit to the 'ScoreThreshold'. The time is--- expressed in epoch time.+-- | The time of the most recent edit to the 'ScoreThreshold'. The time is expressed in epoch time. mlmScoreThresholdLastUpdatedAt :: Lens' MLModel (Maybe UTCTime) mlmScoreThresholdLastUpdatedAt = lens _mlmScoreThresholdLastUpdatedAt (\ s a -> s{_mlmScoreThresholdLastUpdatedAt = a}) . mapping _Time; --- | The time that the 'MLModel' was created. The time is expressed in epoch--- time.+-- | The time that the 'MLModel' was created. The time is expressed in epoch time. mlmCreatedAt :: Lens' MLModel (Maybe UTCTime) mlmCreatedAt = lens _mlmCreatedAt (\ s a -> s{_mlmCreatedAt = a}) . mapping _Time; --- | The location of the data file or directory in Amazon Simple Storage--- Service (Amazon S3).+-- | The location of the data file or directory in Amazon Simple Storage Service (Amazon S3). mlmInputDataLocationS3 :: Lens' MLModel (Maybe Text) mlmInputDataLocationS3 = lens _mlmInputDataLocationS3 (\ s a -> s{_mlmInputDataLocationS3 = a}); @@ -671,17 +598,13 @@ mlmScoreThreshold :: Lens' MLModel (Maybe Double) mlmScoreThreshold = lens _mlmScoreThreshold (\ s a -> s{_mlmScoreThreshold = a}); --- | The algorithm used to train the 'MLModel'. The following algorithm is--- supported:+-- | The algorithm used to train the 'MLModel'. The following algorithm is supported: ----- -   SGD -- Stochastic gradient descent. The goal of SGD is to minimize---     the gradient of the loss function.+-- -   SGD -- Stochastic gradient descent. The goal of SGD is to minimize the gradient of the loss function. mlmAlgorithm :: Lens' MLModel (Maybe Algorithm) mlmAlgorithm = lens _mlmAlgorithm (\ s a -> s{_mlmAlgorithm = a}); --- | The AWS user account from which the 'MLModel' was created. The account--- type can be either an AWS root account or an AWS Identity and Access--- Management (IAM) user account.+-- | The AWS user account from which the 'MLModel' was created. The account type can be either an AWS root account or an AWS Identity and Access Management (IAM) user account. mlmCreatedByIAMUser :: Lens' MLModel (Maybe Text) mlmCreatedByIAMUser = lens _mlmCreatedByIAMUser (\ s a -> s{_mlmCreatedByIAMUser = a}); @@ -693,8 +616,7 @@ mlmEndpointInfo :: Lens' MLModel (Maybe RealtimeEndpointInfo) mlmEndpointInfo = lens _mlmEndpointInfo (\ s a -> s{_mlmEndpointInfo = a}); --- | The ID of the training 'DataSource'. The < CreateMLModel> operation uses--- the 'TrainingDataSourceId'.+-- | The ID of the training 'DataSource'. The < CreateMLModel> operation uses the 'TrainingDataSourceId'. mlmTrainingDataSourceId :: Lens' MLModel (Maybe Text) mlmTrainingDataSourceId = lens _mlmTrainingDataSourceId (\ s a -> s{_mlmTrainingDataSourceId = a}); @@ -702,15 +624,11 @@ mlmMessage :: Lens' MLModel (Maybe Text) mlmMessage = lens _mlmMessage (\ s a -> s{_mlmMessage = a}); --- | Identifies the 'MLModel' category. The following are the available--- types:+-- | Identifies the 'MLModel' category. The following are the available types: ----- -   REGRESSION - Produces a numeric result. For example, \"What listing---     price should a house have?\".--- -   BINARY - Produces one of two possible results. For example, \"Is---     this a child-friendly web site?\".--- -   MULTICLASS - Produces more than two possible results. For example,---     \"Is this a HIGH, LOW or MEDIUM risk trade?\".+-- -   REGRESSION - Produces a numeric result. For example, \"What listing price should a house have?\".+-- -   BINARY - Produces one of two possible results. For example, \"Is this a child-friendly web site?\".+-- -   MULTICLASS - Produces more than two possible results. For example, \"Is this a HIGH, LOW or MEDIUM risk trade?\". mlmMLModelType :: Lens' MLModel (Maybe MLModelType) mlmMLModelType = lens _mlmMLModelType (\ s a -> s{_mlmMLModelType = a}); @@ -739,23 +657,15 @@  instance NFData MLModel --- | Measurements of how well the 'MLModel' performed on known observations.--- One of the following metrics is returned, based on the type of the--- 'MLModel':+-- | Measurements of how well the 'MLModel' performed on known observations. One of the following metrics is returned, based on the type of the 'MLModel': ----- -   BinaryAUC: The binary 'MLModel' uses the Area Under the Curve (AUC)---     technique to measure performance.+-- -   BinaryAUC: The binary 'MLModel' uses the Area Under the Curve (AUC) technique to measure performance. ----- -   RegressionRMSE: The regression 'MLModel' uses the Root Mean Square---     Error (RMSE) technique to measure performance. RMSE measures the---     difference between predicted and actual values for a single---     variable.+-- -   RegressionRMSE: The regression 'MLModel' uses the Root Mean Square Error (RMSE) technique to measure performance. RMSE measures the difference between predicted and actual values for a single variable. ----- -   MulticlassAvgFScore: The multiclass 'MLModel' uses the F1 score---     technique to measure performance.+-- -   MulticlassAvgFScore: The multiclass 'MLModel' uses the F1 score technique to measure performance. ----- For more information about performance metrics, please see the--- <http://docs.aws.amazon.com/machine-learning/latest/dg Amazon Machine Learning Developer Guide>.+-- For more information about performance metrics, please see the <http://docs.aws.amazon.com/machine-learning/latest/dg Amazon Machine Learning Developer Guide>. -- -- /See:/ 'performanceMetrics' smart constructor. newtype PerformanceMetrics = PerformanceMetrics'@@ -791,15 +701,11 @@  -- | The output from a 'Predict' operation: ----- -   'Details' - Contains the following attributes:---     DetailsAttributes.PREDICTIVE_MODEL_TYPE - REGRESSION | BINARY |---     MULTICLASS DetailsAttributes.ALGORITHM - SGD+-- -   'Details' - Contains the following attributes: DetailsAttributes.PREDICTIVE_MODEL_TYPE - REGRESSION | BINARY | MULTICLASS DetailsAttributes.ALGORITHM - SGD ----- -   'PredictedLabel' - Present for either a BINARY or MULTICLASS---     'MLModel' request.+-- -   'PredictedLabel' - Present for either a BINARY or MULTICLASS 'MLModel' request. ----- -   'PredictedScores' - Contains the raw classification score---     corresponding to each label.+-- -   'PredictedScores' - Contains the raw classification score corresponding to each label. -- -- -   'PredictedValue' - Present for a REGRESSION 'MLModel' request. --@@ -862,8 +768,7 @@  instance NFData Prediction --- | The data specification of an Amazon Relational Database Service (Amazon--- RDS) 'DataSource'.+-- | The data specification of an Amazon Relational Database Service (Amazon RDS) 'DataSource'. -- -- /See:/ 'rdsDataSpec' smart constructor. data RDSDataSpec = RDSDataSpec'@@ -933,15 +838,11 @@ rdsdsDataSchemaURI :: Lens' RDSDataSpec (Maybe Text) rdsdsDataSchemaURI = lens _rdsdsDataSchemaURI (\ s a -> s{_rdsdsDataSchemaURI = a}); --- | A JSON string that represents the schema for an Amazon RDS 'DataSource'.--- The 'DataSchema' defines the structure of the observation data in the--- data file(s) referenced in the 'DataSource'.+-- | A JSON string that represents the schema for an Amazon RDS 'DataSource'. The 'DataSchema' defines the structure of the observation data in the data file(s) referenced in the 'DataSource'. -- -- A 'DataSchema' is not required if you specify a 'DataSchemaUri' ----- Define your 'DataSchema' as a series of key-value pairs. 'attributes'--- and 'excludedVariableNames' have an array of key-value pairs for their--- value. Use the following format to define your 'DataSchema'.+-- Define your 'DataSchema' as a series of key-value pairs. 'attributes' and 'excludedVariableNames' have an array of key-value pairs for their value. Use the following format to define your 'DataSchema'. -- -- { \"version\": \"1.0\", --@@ -957,72 +858,47 @@ -- -- \"attributes\": [ ----- { \"fieldName\": \"F1\", \"fieldType\": \"TEXT\" }, { \"fieldName\":--- \"F2\", \"fieldType\": \"NUMERIC\" }, { \"fieldName\": \"F3\",--- \"fieldType\": \"CATEGORICAL\" }, { \"fieldName\": \"F4\",--- \"fieldType\": \"NUMERIC\" }, { \"fieldName\": \"F5\", \"fieldType\":--- \"CATEGORICAL\" }, { \"fieldName\": \"F6\", \"fieldType\": \"TEXT\" }, {--- \"fieldName\": \"F7\", \"fieldType\": \"WEIGHTED_INT_SEQUENCE\" }, {--- \"fieldName\": \"F8\", \"fieldType\": \"WEIGHTED_STRING_SEQUENCE\" } ],+-- { \"fieldName\": \"F1\", \"fieldType\": \"TEXT\" }, { \"fieldName\": \"F2\", \"fieldType\": \"NUMERIC\" }, { \"fieldName\": \"F3\", \"fieldType\": \"CATEGORICAL\" }, { \"fieldName\": \"F4\", \"fieldType\": \"NUMERIC\" }, { \"fieldName\": \"F5\", \"fieldType\": \"CATEGORICAL\" }, { \"fieldName\": \"F6\", \"fieldType\": \"TEXT\" }, { \"fieldName\": \"F7\", \"fieldType\": \"WEIGHTED_INT_SEQUENCE\" }, { \"fieldName\": \"F8\", \"fieldType\": \"WEIGHTED_STRING_SEQUENCE\" } ], -- -- \"excludedVariableNames\": [ \"F6\" ] } rdsdsDataSchema :: Lens' RDSDataSpec (Maybe Text) rdsdsDataSchema = lens _rdsdsDataSchema (\ s a -> s{_rdsdsDataSchema = a}); --- | DataRearrangement - A JSON string that represents the splitting--- requirement of a 'DataSource'.+-- | DataRearrangement - A JSON string that represents the splitting requirement of a 'DataSource'. ----- Sample ---- ' \"{\\\"splitting\\\":{\\\"percentBegin\\\":10,\\\"percentEnd\\\":60}}\"'+-- Sample - ' \"{\\\"splitting\\\":{\\\"percentBegin\\\":10,\\\"percentEnd\\\":60}}\"' rdsdsDataRearrangement :: Lens' RDSDataSpec (Maybe Text) rdsdsDataRearrangement = lens _rdsdsDataRearrangement (\ s a -> s{_rdsdsDataRearrangement = a}); --- | Describes the 'DatabaseName' and 'InstanceIdentifier' of an an Amazon--- RDS database.+-- | Describes the 'DatabaseName' and 'InstanceIdentifier' of an an Amazon RDS database. rdsdsDatabaseInformation :: Lens' RDSDataSpec RDSDatabase rdsdsDatabaseInformation = lens _rdsdsDatabaseInformation (\ s a -> s{_rdsdsDatabaseInformation = a}); --- | The query that is used to retrieve the observation data for the--- 'DataSource'.+-- | The query that is used to retrieve the observation data for the 'DataSource'. rdsdsSelectSqlQuery :: Lens' RDSDataSpec Text rdsdsSelectSqlQuery = lens _rdsdsSelectSqlQuery (\ s a -> s{_rdsdsSelectSqlQuery = a}); --- | The AWS Identity and Access Management (IAM) credentials that are used--- connect to the Amazon RDS database.+-- | The AWS Identity and Access Management (IAM) credentials that are used connect to the Amazon RDS database. rdsdsDatabaseCredentials :: Lens' RDSDataSpec RDSDatabaseCredentials rdsdsDatabaseCredentials = lens _rdsdsDatabaseCredentials (\ s a -> s{_rdsdsDatabaseCredentials = a}); --- | The Amazon S3 location for staging Amazon RDS data. The data retrieved--- from Amazon RDS using 'SelectSqlQuery' is stored in this location.+-- | The Amazon S3 location for staging Amazon RDS data. The data retrieved from Amazon RDS using 'SelectSqlQuery' is stored in this location. rdsdsS3StagingLocation :: Lens' RDSDataSpec Text rdsdsS3StagingLocation = lens _rdsdsS3StagingLocation (\ s a -> s{_rdsdsS3StagingLocation = a}); --- | The role (DataPipelineDefaultResourceRole) assumed by an Amazon Elastic--- Compute Cloud (Amazon EC2) instance to carry out the copy operation from--- Amazon RDS to an Amazon S3 task. For more information, see--- <http://docs.aws.amazon.com/datapipeline/latest/DeveloperGuide/dp-iam-roles.html Role templates>--- for data pipelines.+-- | The role (DataPipelineDefaultResourceRole) assumed by an Amazon Elastic Compute Cloud (Amazon EC2) instance to carry out the copy operation from Amazon RDS to an Amazon S3 task. For more information, see <http://docs.aws.amazon.com/datapipeline/latest/DeveloperGuide/dp-iam-roles.html Role templates> for data pipelines. rdsdsResourceRole :: Lens' RDSDataSpec Text rdsdsResourceRole = lens _rdsdsResourceRole (\ s a -> s{_rdsdsResourceRole = a}); --- | The role (DataPipelineDefaultRole) assumed by AWS Data Pipeline service--- to monitor the progress of the copy task from Amazon RDS to Amazon S3.--- For more information, see--- <http://docs.aws.amazon.com/datapipeline/latest/DeveloperGuide/dp-iam-roles.html Role templates>--- for data pipelines.+-- | The role (DataPipelineDefaultRole) assumed by AWS Data Pipeline service to monitor the progress of the copy task from Amazon RDS to Amazon S3. For more information, see <http://docs.aws.amazon.com/datapipeline/latest/DeveloperGuide/dp-iam-roles.html Role templates> for data pipelines. rdsdsServiceRole :: Lens' RDSDataSpec Text rdsdsServiceRole = lens _rdsdsServiceRole (\ s a -> s{_rdsdsServiceRole = a}); --- | The subnet ID to be used to access a VPC-based RDS DB instance. This--- attribute is used by Data Pipeline to carry out the copy task from--- Amazon RDS to Amazon S3.+-- | The subnet ID to be used to access a VPC-based RDS DB instance. This attribute is used by Data Pipeline to carry out the copy task from Amazon RDS to Amazon S3. rdsdsSubnetId :: Lens' RDSDataSpec Text rdsdsSubnetId = lens _rdsdsSubnetId (\ s a -> s{_rdsdsSubnetId = a}); --- | The security group IDs to be used to access a VPC-based RDS DB instance.--- Ensure that there are appropriate ingress rules set up to allow access--- to the RDS DB instance. This attribute is used by Data Pipeline to carry--- out the copy operation from Amazon RDS to an Amazon S3 task.+-- | The security group IDs to be used to access a VPC-based RDS DB instance. Ensure that there are appropriate ingress rules set up to allow access to the RDS DB instance. This attribute is used by Data Pipeline to carry out the copy operation from Amazon RDS to an Amazon S3 task. rdsdsSecurityGroupIds :: Lens' RDSDataSpec [Text] rdsdsSecurityGroupIds = lens _rdsdsSecurityGroupIds (\ s a -> s{_rdsdsSecurityGroupIds = a}) . _Coerce; @@ -1185,14 +1061,11 @@     , _rmServiceRole = Nothing     } --- | The SQL query that is supplied during < CreateDataSourceFromRDS>.--- Returns only if 'Verbose' is true in 'GetDataSourceInput'.+-- | The SQL query that is supplied during < CreateDataSourceFromRDS>. Returns only if 'Verbose' is true in 'GetDataSourceInput'. rmSelectSqlQuery :: Lens' RDSMetadata (Maybe Text) rmSelectSqlQuery = lens _rmSelectSqlQuery (\ s a -> s{_rmSelectSqlQuery = a}); --- | The ID of the Data Pipeline instance that is used to carry to copy data--- from Amazon RDS to Amazon S3. You can use the ID to find details about--- the instance in the Data Pipeline console.+-- | The ID of the Data Pipeline instance that is used to carry to copy data from Amazon RDS to Amazon S3. You can use the ID to find details about the instance in the Data Pipeline console. rmDataPipelineId :: Lens' RDSMetadata (Maybe Text) rmDataPipelineId = lens _rmDataPipelineId (\ s a -> s{_rmDataPipelineId = a}); @@ -1204,19 +1077,11 @@ rmDatabaseUserName :: Lens' RDSMetadata (Maybe Text) rmDatabaseUserName = lens _rmDatabaseUserName (\ s a -> s{_rmDatabaseUserName = a}); --- | The role (DataPipelineDefaultResourceRole) assumed by an Amazon EC2--- instance to carry out the copy task from Amazon RDS to Amazon S3. For--- more information, see--- <http://docs.aws.amazon.com/datapipeline/latest/DeveloperGuide/dp-iam-roles.html Role templates>--- for data pipelines.+-- | The role (DataPipelineDefaultResourceRole) assumed by an Amazon EC2 instance to carry out the copy task from Amazon RDS to Amazon S3. For more information, see <http://docs.aws.amazon.com/datapipeline/latest/DeveloperGuide/dp-iam-roles.html Role templates> for data pipelines. rmResourceRole :: Lens' RDSMetadata (Maybe Text) rmResourceRole = lens _rmResourceRole (\ s a -> s{_rmResourceRole = a}); --- | The role (DataPipelineDefaultRole) assumed by the Data Pipeline service--- to monitor the progress of the copy task from Amazon RDS to Amazon S3.--- For more information, see--- <http://docs.aws.amazon.com/datapipeline/latest/DeveloperGuide/dp-iam-roles.html Role templates>--- for data pipelines.+-- | The role (DataPipelineDefaultRole) assumed by the Data Pipeline service to monitor the progress of the copy task from Amazon RDS to Amazon S3. For more information, see <http://docs.aws.amazon.com/datapipeline/latest/DeveloperGuide/dp-iam-roles.html Role templates> for data pipelines. rmServiceRole :: Lens' RDSMetadata (Maybe Text) rmServiceRole = lens _rmServiceRole (\ s a -> s{_rmServiceRole = a}); @@ -1266,23 +1131,19 @@     , _reiPeakRequestsPerSecond = Nothing     } --- | The time that the request to create the real-time endpoint for the--- 'MLModel' was received. The time is expressed in epoch time.+-- | The time that the request to create the real-time endpoint for the 'MLModel' was received. The time is expressed in epoch time. reiCreatedAt :: Lens' RealtimeEndpointInfo (Maybe UTCTime) reiCreatedAt = lens _reiCreatedAt (\ s a -> s{_reiCreatedAt = a}) . mapping _Time; --- | The URI that specifies where to send real-time prediction requests for--- the 'MLModel'.+-- | The URI that specifies where to send real-time prediction requests for the 'MLModel'. -- -- Note ----- The application must wait until the real-time endpoint is ready before--- using this URI.+-- The application must wait until the real-time endpoint is ready before using this URI. reiEndpointURL :: Lens' RealtimeEndpointInfo (Maybe Text) reiEndpointURL = lens _reiEndpointURL (\ s a -> s{_reiEndpointURL = a}); --- | The current status of the real-time endpoint for the 'MLModel'. This--- element can have one of the following values:+-- | The current status of the real-time endpoint for the 'MLModel'. This element can have one of the following values: -- -- -   NONE - Endpoint does not exist or was previously deleted. -- -   READY - Endpoint is ready to be used for real-time predictions.@@ -1290,8 +1151,7 @@ reiEndpointStatus :: Lens' RealtimeEndpointInfo (Maybe RealtimeEndpointStatus) reiEndpointStatus = lens _reiEndpointStatus (\ s a -> s{_reiEndpointStatus = a}); --- | The maximum processing rate for the real-time endpoint for 'MLModel',--- measured in incoming requests per second.+-- | The maximum processing rate for the real-time endpoint for 'MLModel', measured in incoming requests per second. reiPeakRequestsPerSecond :: Lens' RealtimeEndpointInfo (Maybe Int) reiPeakRequestsPerSecond = lens _reiPeakRequestsPerSecond (\ s a -> s{_reiPeakRequestsPerSecond = a}); @@ -1359,15 +1219,11 @@ rDataSchemaURI :: Lens' RedshiftDataSpec (Maybe Text) rDataSchemaURI = lens _rDataSchemaURI (\ s a -> s{_rDataSchemaURI = a}); --- | A JSON string that represents the schema for an Amazon Redshift--- 'DataSource'. The 'DataSchema' defines the structure of the observation--- data in the data file(s) referenced in the 'DataSource'.+-- | A JSON string that represents the schema for an Amazon Redshift 'DataSource'. The 'DataSchema' defines the structure of the observation data in the data file(s) referenced in the 'DataSource'. -- -- A 'DataSchema' is not required if you specify a 'DataSchemaUri'. ----- Define your 'DataSchema' as a series of key-value pairs. 'attributes'--- and 'excludedVariableNames' have an array of key-value pairs for their--- value. Use the following format to define your 'DataSchema'.+-- Define your 'DataSchema' as a series of key-value pairs. 'attributes' and 'excludedVariableNames' have an array of key-value pairs for their value. Use the following format to define your 'DataSchema'. -- -- { \"version\": \"1.0\", --@@ -1383,13 +1239,7 @@ -- -- \"attributes\": [ ----- { \"fieldName\": \"F1\", \"fieldType\": \"TEXT\" }, { \"fieldName\":--- \"F2\", \"fieldType\": \"NUMERIC\" }, { \"fieldName\": \"F3\",--- \"fieldType\": \"CATEGORICAL\" }, { \"fieldName\": \"F4\",--- \"fieldType\": \"NUMERIC\" }, { \"fieldName\": \"F5\", \"fieldType\":--- \"CATEGORICAL\" }, { \"fieldName\": \"F6\", \"fieldType\": \"TEXT\" }, {--- \"fieldName\": \"F7\", \"fieldType\": \"WEIGHTED_INT_SEQUENCE\" }, {--- \"fieldName\": \"F8\", \"fieldType\": \"WEIGHTED_STRING_SEQUENCE\" } ],+-- { \"fieldName\": \"F1\", \"fieldType\": \"TEXT\" }, { \"fieldName\": \"F2\", \"fieldType\": \"NUMERIC\" }, { \"fieldName\": \"F3\", \"fieldType\": \"CATEGORICAL\" }, { \"fieldName\": \"F4\", \"fieldType\": \"NUMERIC\" }, { \"fieldName\": \"F5\", \"fieldType\": \"CATEGORICAL\" }, { \"fieldName\": \"F6\", \"fieldType\": \"TEXT\" }, { \"fieldName\": \"F7\", \"fieldType\": \"WEIGHTED_INT_SEQUENCE\" }, { \"fieldName\": \"F8\", \"fieldType\": \"WEIGHTED_STRING_SEQUENCE\" } ], -- -- \"excludedVariableNames\": [ \"F6\" ] } rDataSchema :: Lens' RedshiftDataSpec (Maybe Text)@@ -1399,23 +1249,19 @@ rDataRearrangement :: Lens' RedshiftDataSpec (Maybe Text) rDataRearrangement = lens _rDataRearrangement (\ s a -> s{_rDataRearrangement = a}); --- | Describes the 'DatabaseName' and 'ClusterIdentifier' for an Amazon--- Redshift 'DataSource'.+-- | Describes the 'DatabaseName' and 'ClusterIdentifier' for an Amazon Redshift 'DataSource'. rDatabaseInformation :: Lens' RedshiftDataSpec RedshiftDatabase rDatabaseInformation = lens _rDatabaseInformation (\ s a -> s{_rDatabaseInformation = a}); --- | Describes the SQL Query to execute on an Amazon Redshift database for an--- Amazon Redshift 'DataSource'.+-- | Describes the SQL Query to execute on an Amazon Redshift database for an Amazon Redshift 'DataSource'. rSelectSqlQuery :: Lens' RedshiftDataSpec Text rSelectSqlQuery = lens _rSelectSqlQuery (\ s a -> s{_rSelectSqlQuery = a}); --- | Describes AWS Identity and Access Management (IAM) credentials that are--- used connect to the Amazon Redshift database.+-- | Describes AWS Identity and Access Management (IAM) credentials that are used connect to the Amazon Redshift database. rDatabaseCredentials :: Lens' RedshiftDataSpec RedshiftDatabaseCredentials rDatabaseCredentials = lens _rDatabaseCredentials (\ s a -> s{_rDatabaseCredentials = a}); --- | Describes an Amazon S3 location to store the result set of the--- 'SelectSqlQuery' query.+-- | Describes an Amazon S3 location to store the result set of the 'SelectSqlQuery' query. rS3StagingLocation :: Lens' RedshiftDataSpec Text rS3StagingLocation = lens _rS3StagingLocation (\ s a -> s{_rS3StagingLocation = a}); @@ -1437,8 +1283,7 @@                     ("DatabaseCredentials" .= _rDatabaseCredentials),                   Just ("S3StagingLocation" .= _rS3StagingLocation)]) --- | Describes the database details required to connect to an Amazon Redshift--- database.+-- | Describes the database details required to connect to an Amazon Redshift database. -- -- /See:/ 'redshiftDatabase' smart constructor. data RedshiftDatabase = RedshiftDatabase'@@ -1489,8 +1334,7 @@                  [Just ("DatabaseName" .= _rdDatabaseName),                   Just ("ClusterIdentifier" .= _rdClusterIdentifier)]) --- | Describes the database credentials for connecting to a database on an--- Amazon Redshift cluster.+-- | Describes the database credentials for connecting to a database on an Amazon Redshift cluster. -- -- /See:/ 'redshiftDatabaseCredentials' smart constructor. data RedshiftDatabaseCredentials = RedshiftDatabaseCredentials'@@ -1561,8 +1405,7 @@     , _redDatabaseUserName = Nothing     } --- | The SQL query that is specified during < CreateDataSourceFromRedshift>.--- Returns only if 'Verbose' is true in GetDataSourceInput.+-- | The SQL query that is specified during < CreateDataSourceFromRedshift>. Returns only if 'Verbose' is true in GetDataSourceInput. redSelectSqlQuery :: Lens' RedshiftMetadata (Maybe Text) redSelectSqlQuery = lens _redSelectSqlQuery (\ s a -> s{_redSelectSqlQuery = a}); @@ -1619,13 +1462,9 @@     , _sdsDataLocationS3 = pDataLocationS3_     } --- | A JSON string that represents the schema for an Amazon S3 'DataSource'.--- The 'DataSchema' defines the structure of the observation data in the--- data file(s) referenced in the 'DataSource'.+-- | A JSON string that represents the schema for an Amazon S3 'DataSource'. The 'DataSchema' defines the structure of the observation data in the data file(s) referenced in the 'DataSource'. ----- Define your 'DataSchema' as a series of key-value pairs. 'attributes'--- and 'excludedVariableNames' have an array of key-value pairs for their--- value. Use the following format to define your 'DataSchema'.+-- Define your 'DataSchema' as a series of key-value pairs. 'attributes' and 'excludedVariableNames' have an array of key-value pairs for their value. Use the following format to define your 'DataSchema'. -- -- { \"version\": \"1.0\", --@@ -1641,13 +1480,7 @@ -- -- \"attributes\": [ ----- { \"fieldName\": \"F1\", \"fieldType\": \"TEXT\" }, { \"fieldName\":--- \"F2\", \"fieldType\": \"NUMERIC\" }, { \"fieldName\": \"F3\",--- \"fieldType\": \"CATEGORICAL\" }, { \"fieldName\": \"F4\",--- \"fieldType\": \"NUMERIC\" }, { \"fieldName\": \"F5\", \"fieldType\":--- \"CATEGORICAL\" }, { \"fieldName\": \"F6\", \"fieldType\": \"TEXT\" }, {--- \"fieldName\": \"F7\", \"fieldType\": \"WEIGHTED_INT_SEQUENCE\" }, {--- \"fieldName\": \"F8\", \"fieldType\": \"WEIGHTED_STRING_SEQUENCE\" } ],+-- { \"fieldName\": \"F1\", \"fieldType\": \"TEXT\" }, { \"fieldName\": \"F2\", \"fieldType\": \"NUMERIC\" }, { \"fieldName\": \"F3\", \"fieldType\": \"CATEGORICAL\" }, { \"fieldName\": \"F4\", \"fieldType\": \"NUMERIC\" }, { \"fieldName\": \"F5\", \"fieldType\": \"CATEGORICAL\" }, { \"fieldName\": \"F6\", \"fieldType\": \"TEXT\" }, { \"fieldName\": \"F7\", \"fieldType\": \"WEIGHTED_INT_SEQUENCE\" }, { \"fieldName\": \"F8\", \"fieldType\": \"WEIGHTED_STRING_SEQUENCE\" } ], -- -- \"excludedVariableNames\": [ \"F6\" ] } sdsDataSchema :: Lens' S3DataSpec (Maybe Text)@@ -1661,9 +1494,7 @@ sdsDataRearrangement :: Lens' S3DataSpec (Maybe Text) sdsDataRearrangement = lens _sdsDataRearrangement (\ s a -> s{_sdsDataRearrangement = a}); --- | The location of the data file(s) used by a 'DataSource'. The URI--- specifies a data file or an Amazon Simple Storage Service (Amazon S3)--- directory or bucket containing data files.+-- | The location of the data file(s) used by a 'DataSource'. The URI specifies a data file or an Amazon Simple Storage Service (Amazon S3) directory or bucket containing data files. sdsDataLocationS3 :: Lens' S3DataSpec Text sdsDataLocationS3 = lens _sdsDataLocationS3 (\ s a -> s{_sdsDataLocationS3 = a});
gen/Network/AWS/MachineLearning/Types/Sum.hs view
@@ -19,8 +19,7 @@  import           Network.AWS.Prelude --- | The function used to train a 'MLModel'. Training choices supported by--- Amazon ML include the following:+-- | The function used to train a 'MLModel'. Training choices supported by Amazon ML include the following: -- -- -   SGD - Stochastic Gradient Descent. -- -   RandomForest - Random forest of decision trees.@@ -47,23 +46,15 @@ instance FromJSON Algorithm where     parseJSON = parseJSONText "Algorithm" --- | A list of the variables to use in searching or filtering--- 'BatchPrediction'.+-- | A list of the variables to use in searching or filtering 'BatchPrediction'. ----- -   'CreatedAt' - Sets the search criteria to 'BatchPrediction' creation---     date.+-- -   'CreatedAt' - Sets the search criteria to 'BatchPrediction' creation date. -- -   'Status' - Sets the search criteria to 'BatchPrediction' status.--- -   'Name' - Sets the search criteria to the contents of---     'BatchPrediction' ____ 'Name'.--- -   'IAMUser' - Sets the search criteria to the user account that---     invoked the 'BatchPrediction' creation.--- -   'MLModelId' - Sets the search criteria to the 'MLModel' used in the---     'BatchPrediction'.--- -   'DataSourceId' - Sets the search criteria to the 'DataSource' used---     in the 'BatchPrediction'.--- -   'DataURI' - Sets the search criteria to the data file(s) used in the---     'BatchPrediction'. The URL can identify either a file or an Amazon---     Simple Storage Service (Amazon S3) bucket or directory.+-- -   'Name' - Sets the search criteria to the contents of 'BatchPrediction' ____ 'Name'.+-- -   'IAMUser' - Sets the search criteria to the user account that invoked the 'BatchPrediction' creation.+-- -   'MLModelId' - Sets the search criteria to the 'MLModel' used in the 'BatchPrediction'.+-- -   'DataSourceId' - Sets the search criteria to the 'DataSource' used in the 'BatchPrediction'.+-- -   'DataURI' - Sets the search criteria to the data file(s) used in the 'BatchPrediction'. The URL can identify either a file or an Amazon Simple Storage Service (Amazon S3) bucket or directory. data BatchPredictionFilterVariable     = BatchCreatedAt     | BatchDataSourceId@@ -110,16 +101,11 @@  -- | A list of the variables to use in searching or filtering 'DataSource'. ----- -   'CreatedAt' - Sets the search criteria to 'DataSource' creation---     date.+-- -   'CreatedAt' - Sets the search criteria to 'DataSource' creation date. -- -   'Status' - Sets the search criteria to 'DataSource' status.--- -   'Name' - Sets the search criteria to the contents of 'DataSource'---     ____ 'Name'.--- -   'DataUri' - Sets the search criteria to the URI of data files used---     to create the 'DataSource'. The URI can identify either a file or an---     Amazon Simple Storage Service (Amazon S3) bucket or directory.--- -   'IAMUser' - Sets the search criteria to the user account that---     invoked the 'DataSource' creation.+-- -   'Name' - Sets the search criteria to the contents of 'DataSource' ____ 'Name'.+-- -   'DataUri' - Sets the search criteria to the URI of data files used to create the 'DataSource'. The URI can identify either a file or an Amazon Simple Storage Service (Amazon S3) bucket or directory.+-- -   'IAMUser' - Sets the search criteria to the user account that invoked the 'DataSource' creation. -- -- Note --@@ -162,9 +148,7 @@ instance ToJSON DataSourceFilterVariable where     toJSON = toJSONText --- | Contains the key values of 'DetailsMap': PredictiveModelType - Indicates--- the type of the 'MLModel'. Algorithm - Indicates the algorithm was used--- for the 'MLModel'.+-- | Contains the key values of 'DetailsMap': PredictiveModelType - Indicates the type of the 'MLModel'. Algorithm - Indicates the algorithm was used for the 'MLModel'. data DetailsAttributes     = Algorithm     | PredictiveModelType@@ -235,20 +219,13 @@  -- | A list of the variables to use in searching or filtering 'Evaluation'. ----- -   'CreatedAt' - Sets the search criteria to 'Evaluation' creation---     date.+-- -   'CreatedAt' - Sets the search criteria to 'Evaluation' creation date. -- -   'Status' - Sets the search criteria to 'Evaluation' status.--- -   'Name' - Sets the search criteria to the contents of 'Evaluation'---     ____ 'Name'.--- -   'IAMUser' - Sets the search criteria to the user account that---     invoked an evaluation.--- -   'MLModelId' - Sets the search criteria to the 'Predictor' that was---     evaluated.--- -   'DataSourceId' - Sets the search criteria to the 'DataSource' used---     in evaluation.--- -   'DataUri' - Sets the search criteria to the data file(s) used in---     evaluation. The URL can identify either a file or an Amazon Simple---     Storage Service (Amazon S3) bucket or directory.+-- -   'Name' - Sets the search criteria to the contents of 'Evaluation' ____ 'Name'.+-- -   'IAMUser' - Sets the search criteria to the user account that invoked an evaluation.+-- -   'MLModelId' - Sets the search criteria to the 'Predictor' that was evaluated.+-- -   'DataSourceId' - Sets the search criteria to the 'DataSource' used in evaluation.+-- -   'DataUri' - Sets the search criteria to the data file(s) used in evaluation. The URL can identify either a file or an Amazon Simple Storage Service (Amazon S3) bucket or directory. data EvaluationFilterVariable     = EvalCreatedAt     | EvalDataSourceId@@ -407,8 +384,7 @@ instance FromJSON RealtimeEndpointStatus where     parseJSON = parseJSONText "RealtimeEndpointStatus" --- | The sort order specified in a listing condition. Possible values include--- the following:+-- | The sort order specified in a listing condition. Possible values include the following: -- -- -   'asc' - Present the information in ascending order (from A-Z). -- -   'dsc' - Present the information in descending order (from Z-A).
gen/Network/AWS/MachineLearning/UpdateBatchPrediction.hs view
@@ -20,8 +20,7 @@ -- -- Updates the 'BatchPredictionName' of a 'BatchPrediction'. ----- You can use the < GetBatchPrediction> operation to view the contents of--- the updated data element.+-- You can use the < GetBatchPrediction> operation to view the contents of the updated data element. module Network.AWS.MachineLearning.UpdateBatchPrediction     (     -- * Creating a Request@@ -117,8 +116,7 @@  -- | Represents the output of an < UpdateBatchPrediction> operation. ----- You can see the updated content by using the < GetBatchPrediction>--- operation.+-- You can see the updated content by using the < GetBatchPrediction> operation. -- -- /See:/ 'updateBatchPredictionResponse' smart constructor. data UpdateBatchPredictionResponse = UpdateBatchPredictionResponse'@@ -142,9 +140,7 @@     , _ubprsResponseStatus = pResponseStatus_     } --- | The ID assigned to the 'BatchPrediction' during creation. This value--- should be identical to the value of the 'BatchPredictionId' in the--- request.+-- | The ID assigned to the 'BatchPrediction' during creation. This value should be identical to the value of the 'BatchPredictionId' in the request. ubprsBatchPredictionId :: Lens' UpdateBatchPredictionResponse (Maybe Text) ubprsBatchPredictionId = lens _ubprsBatchPredictionId (\ s a -> s{_ubprsBatchPredictionId = a});
gen/Network/AWS/MachineLearning/UpdateDataSource.hs view
@@ -20,8 +20,7 @@ -- -- Updates the 'DataSourceName' of a 'DataSource'. ----- You can use the < GetDataSource> operation to view the contents of the--- updated data element.+-- You can use the < GetDataSource> operation to view the contents of the updated data element. module Network.AWS.MachineLearning.UpdateDataSource     (     -- * Creating a Request@@ -73,8 +72,7 @@ udsDataSourceId :: Lens' UpdateDataSource Text udsDataSourceId = lens _udsDataSourceId (\ s a -> s{_udsDataSourceId = a}); --- | A new user-supplied name or description of the 'DataSource' that will--- replace the current description.+-- | A new user-supplied name or description of the 'DataSource' that will replace the current description. udsDataSourceName :: Lens' UpdateDataSource Text udsDataSourceName = lens _udsDataSourceName (\ s a -> s{_udsDataSourceName = a}); @@ -115,8 +113,7 @@  -- | Represents the output of an < UpdateDataSource> operation. ----- You can see the updated content by using the < GetBatchPrediction>--- operation.+-- You can see the updated content by using the < GetBatchPrediction> operation. -- -- /See:/ 'updateDataSourceResponse' smart constructor. data UpdateDataSourceResponse = UpdateDataSourceResponse'@@ -140,8 +137,7 @@     , _udsrsResponseStatus = pResponseStatus_     } --- | The ID assigned to the 'DataSource' during creation. This value should--- be identical to the value of the 'DataSourceID' in the request.+-- | The ID assigned to the 'DataSource' during creation. This value should be identical to the value of the 'DataSourceID' in the request. udsrsDataSourceId :: Lens' UpdateDataSourceResponse (Maybe Text) udsrsDataSourceId = lens _udsrsDataSourceId (\ s a -> s{_udsrsDataSourceId = a});
gen/Network/AWS/MachineLearning/UpdateEvaluation.hs view
@@ -20,8 +20,7 @@ -- -- Updates the 'EvaluationName' of an 'Evaluation'. ----- You can use the < GetEvaluation> operation to view the contents of the--- updated data element.+-- You can use the < GetEvaluation> operation to view the contents of the updated data element. module Network.AWS.MachineLearning.UpdateEvaluation     (     -- * Creating a Request@@ -73,8 +72,7 @@ ueEvaluationId :: Lens' UpdateEvaluation Text ueEvaluationId = lens _ueEvaluationId (\ s a -> s{_ueEvaluationId = a}); --- | A new user-supplied name or description of the 'Evaluation' that will--- replace the current content.+-- | A new user-supplied name or description of the 'Evaluation' that will replace the current content. ueEvaluationName :: Lens' UpdateEvaluation Text ueEvaluationName = lens _ueEvaluationName (\ s a -> s{_ueEvaluationName = a}); @@ -139,8 +137,7 @@     , _uersResponseStatus = pResponseStatus_     } --- | The ID assigned to the 'Evaluation' during creation. This value should--- be identical to the value of the 'Evaluation' in the request.+-- | The ID assigned to the 'Evaluation' during creation. This value should be identical to the value of the 'Evaluation' in the request. uersEvaluationId :: Lens' UpdateEvaluationResponse (Maybe Text) uersEvaluationId = lens _uersEvaluationId (\ s a -> s{_uersEvaluationId = a});
gen/Network/AWS/MachineLearning/UpdateMLModel.hs view
@@ -20,8 +20,7 @@ -- -- Updates the 'MLModelName' and the 'ScoreThreshold' of an 'MLModel'. ----- You can use the < GetMLModel> operation to view the contents of the--- updated data element.+-- You can use the < GetMLModel> operation to view the contents of the updated data element. module Network.AWS.MachineLearning.UpdateMLModel     (     -- * Creating a Request@@ -77,13 +76,9 @@ umlmMLModelName :: Lens' UpdateMLModel (Maybe Text) umlmMLModelName = lens _umlmMLModelName (\ s a -> s{_umlmMLModelName = a}); --- | The 'ScoreThreshold' used in binary classification 'MLModel' that marks--- the boundary between a positive prediction and a negative prediction.+-- | The 'ScoreThreshold' used in binary classification 'MLModel' that marks the boundary between a positive prediction and a negative prediction. ----- Output values greater than or equal to the 'ScoreThreshold' receive a--- positive result from the 'MLModel', such as 'true'. Output values less--- than the 'ScoreThreshold' receive a negative response from the--- 'MLModel', such as 'false'.+-- Output values greater than or equal to the 'ScoreThreshold' receive a positive result from the 'MLModel', such as 'true'. Output values less than the 'ScoreThreshold' receive a negative response from the 'MLModel', such as 'false'. umlmScoreThreshold :: Lens' UpdateMLModel (Maybe Double) umlmScoreThreshold = lens _umlmScoreThreshold (\ s a -> s{_umlmScoreThreshold = a}); @@ -153,8 +148,7 @@     , _umlmrsResponseStatus = pResponseStatus_     } --- | The ID assigned to the 'MLModel' during creation. This value should be--- identical to the value of the 'MLModelID' in the request.+-- | The ID assigned to the 'MLModel' during creation. This value should be identical to the value of the 'MLModelID' in the request. umlmrsMLModelId :: Lens' UpdateMLModelResponse (Maybe Text) umlmrsMLModelId = lens _umlmrsMLModelId (\ s a -> s{_umlmrsMLModelId = a});
test/Test/AWS/Gen/MachineLearning.hs view
@@ -28,157 +28,157 @@ -- fixtures :: TestTree -- fixtures = --     [ testGroup "request"---         [ testUpdateDataSource $+--         [ requestUpdateDataSource $ --             updateDataSource -----         , testDeleteDataSource $+--         , requestDeleteDataSource $ --             deleteDataSource -----         , testCreateDataSourceFromRedshift $+--         , requestCreateDataSourceFromRedshift $ --             createDataSourceFromRedshift -----         , testCreateDataSourceFromS3 $+--         , requestCreateDataSourceFromS3 $ --             createDataSourceFromS3 -----         , testCreateMLModel $+--         , requestCreateMLModel $ --             createMLModel -----         , testDeleteBatchPrediction $+--         , requestDeleteBatchPrediction $ --             deleteBatchPrediction -----         , testUpdateBatchPrediction $+--         , requestUpdateBatchPrediction $ --             updateBatchPrediction -----         , testGetMLModel $+--         , requestGetMLModel $ --             getMLModel -----         , testGetDataSource $+--         , requestGetDataSource $ --             getDataSource -----         , testUpdateEvaluation $+--         , requestUpdateEvaluation $ --             updateEvaluation -----         , testDeleteEvaluation $+--         , requestDeleteEvaluation $ --             deleteEvaluation -----         , testDeleteMLModel $+--         , requestDeleteMLModel $ --             deleteMLModel -----         , testUpdateMLModel $+--         , requestUpdateMLModel $ --             updateMLModel -----         , testGetBatchPrediction $+--         , requestGetBatchPrediction $ --             getBatchPrediction -----         , testDescribeBatchPredictions $+--         , requestDescribeBatchPredictions $ --             describeBatchPredictions -----         , testCreateDataSourceFromRDS $+--         , requestCreateDataSourceFromRDS $ --             createDataSourceFromRDS -----         , testCreateEvaluation $+--         , requestCreateEvaluation $ --             createEvaluation -----         , testPredict $+--         , requestPredict $ --             predict -----         , testDeleteRealtimeEndpoint $+--         , requestDeleteRealtimeEndpoint $ --             deleteRealtimeEndpoint -----         , testCreateBatchPrediction $+--         , requestCreateBatchPrediction $ --             createBatchPrediction -----         , testGetEvaluation $+--         , requestGetEvaluation $ --             getEvaluation -----         , testDescribeEvaluations $+--         , requestDescribeEvaluations $ --             describeEvaluations -----         , testCreateRealtimeEndpoint $+--         , requestCreateRealtimeEndpoint $ --             createRealtimeEndpoint -----         , testDescribeMLModels $+--         , requestDescribeMLModels $ --             describeMLModels -----         , testDescribeDataSources $+--         , requestDescribeDataSources $ --             describeDataSources -- --           ]  --     , testGroup "response"---         [ testUpdateDataSourceResponse $+--         [ responseUpdateDataSource $ --             updateDataSourceResponse -----         , testDeleteDataSourceResponse $+--         , responseDeleteDataSource $ --             deleteDataSourceResponse -----         , testCreateDataSourceFromRedshiftResponse $+--         , responseCreateDataSourceFromRedshift $ --             createDataSourceFromRedshiftResponse -----         , testCreateDataSourceFromS3Response $+--         , responseCreateDataSourceFromS3 $ --             createDataSourceFromS3Response -----         , testCreateMLModelResponse $+--         , responseCreateMLModel $ --             createMLModelResponse -----         , testDeleteBatchPredictionResponse $+--         , responseDeleteBatchPrediction $ --             deleteBatchPredictionResponse -----         , testUpdateBatchPredictionResponse $+--         , responseUpdateBatchPrediction $ --             updateBatchPredictionResponse -----         , testGetMLModelResponse $+--         , responseGetMLModel $ --             getMLModelResponse -----         , testGetDataSourceResponse $+--         , responseGetDataSource $ --             getDataSourceResponse -----         , testUpdateEvaluationResponse $+--         , responseUpdateEvaluation $ --             updateEvaluationResponse -----         , testDeleteEvaluationResponse $+--         , responseDeleteEvaluation $ --             deleteEvaluationResponse -----         , testDeleteMLModelResponse $+--         , responseDeleteMLModel $ --             deleteMLModelResponse -----         , testUpdateMLModelResponse $+--         , responseUpdateMLModel $ --             updateMLModelResponse -----         , testGetBatchPredictionResponse $+--         , responseGetBatchPrediction $ --             getBatchPredictionResponse -----         , testDescribeBatchPredictionsResponse $+--         , responseDescribeBatchPredictions $ --             describeBatchPredictionsResponse -----         , testCreateDataSourceFromRDSResponse $+--         , responseCreateDataSourceFromRDS $ --             createDataSourceFromRDSResponse -----         , testCreateEvaluationResponse $+--         , responseCreateEvaluation $ --             createEvaluationResponse -----         , testPredictResponse $+--         , responsePredict $ --             predictResponse -----         , testDeleteRealtimeEndpointResponse $+--         , responseDeleteRealtimeEndpoint $ --             deleteRealtimeEndpointResponse -----         , testCreateBatchPredictionResponse $+--         , responseCreateBatchPrediction $ --             createBatchPredictionResponse -----         , testGetEvaluationResponse $+--         , responseGetEvaluation $ --             getEvaluationResponse -----         , testDescribeEvaluationsResponse $+--         , responseDescribeEvaluations $ --             describeEvaluationsResponse -----         , testCreateRealtimeEndpointResponse $+--         , responseCreateRealtimeEndpoint $ --             createRealtimeEndpointResponse -----         , testDescribeMLModelsResponse $+--         , responseDescribeMLModels $ --             describeMLModelsResponse -----         , testDescribeDataSourcesResponse $+--         , responseDescribeDataSources $ --             describeDataSourcesResponse -- --           ]@@ -186,303 +186,303 @@  -- Requests -testUpdateDataSource :: UpdateDataSource -> TestTree-testUpdateDataSource = req+requestUpdateDataSource :: UpdateDataSource -> TestTree+requestUpdateDataSource = req     "UpdateDataSource"     "fixture/UpdateDataSource.yaml" -testDeleteDataSource :: DeleteDataSource -> TestTree-testDeleteDataSource = req+requestDeleteDataSource :: DeleteDataSource -> TestTree+requestDeleteDataSource = req     "DeleteDataSource"     "fixture/DeleteDataSource.yaml" -testCreateDataSourceFromRedshift :: CreateDataSourceFromRedshift -> TestTree-testCreateDataSourceFromRedshift = req+requestCreateDataSourceFromRedshift :: CreateDataSourceFromRedshift -> TestTree+requestCreateDataSourceFromRedshift = req     "CreateDataSourceFromRedshift"     "fixture/CreateDataSourceFromRedshift.yaml" -testCreateDataSourceFromS3 :: CreateDataSourceFromS3 -> TestTree-testCreateDataSourceFromS3 = req+requestCreateDataSourceFromS3 :: CreateDataSourceFromS3 -> TestTree+requestCreateDataSourceFromS3 = req     "CreateDataSourceFromS3"     "fixture/CreateDataSourceFromS3.yaml" -testCreateMLModel :: CreateMLModel -> TestTree-testCreateMLModel = req+requestCreateMLModel :: CreateMLModel -> TestTree+requestCreateMLModel = req     "CreateMLModel"     "fixture/CreateMLModel.yaml" -testDeleteBatchPrediction :: DeleteBatchPrediction -> TestTree-testDeleteBatchPrediction = req+requestDeleteBatchPrediction :: DeleteBatchPrediction -> TestTree+requestDeleteBatchPrediction = req     "DeleteBatchPrediction"     "fixture/DeleteBatchPrediction.yaml" -testUpdateBatchPrediction :: UpdateBatchPrediction -> TestTree-testUpdateBatchPrediction = req+requestUpdateBatchPrediction :: UpdateBatchPrediction -> TestTree+requestUpdateBatchPrediction = req     "UpdateBatchPrediction"     "fixture/UpdateBatchPrediction.yaml" -testGetMLModel :: GetMLModel -> TestTree-testGetMLModel = req+requestGetMLModel :: GetMLModel -> TestTree+requestGetMLModel = req     "GetMLModel"     "fixture/GetMLModel.yaml" -testGetDataSource :: GetDataSource -> TestTree-testGetDataSource = req+requestGetDataSource :: GetDataSource -> TestTree+requestGetDataSource = req     "GetDataSource"     "fixture/GetDataSource.yaml" -testUpdateEvaluation :: UpdateEvaluation -> TestTree-testUpdateEvaluation = req+requestUpdateEvaluation :: UpdateEvaluation -> TestTree+requestUpdateEvaluation = req     "UpdateEvaluation"     "fixture/UpdateEvaluation.yaml" -testDeleteEvaluation :: DeleteEvaluation -> TestTree-testDeleteEvaluation = req+requestDeleteEvaluation :: DeleteEvaluation -> TestTree+requestDeleteEvaluation = req     "DeleteEvaluation"     "fixture/DeleteEvaluation.yaml" -testDeleteMLModel :: DeleteMLModel -> TestTree-testDeleteMLModel = req+requestDeleteMLModel :: DeleteMLModel -> TestTree+requestDeleteMLModel = req     "DeleteMLModel"     "fixture/DeleteMLModel.yaml" -testUpdateMLModel :: UpdateMLModel -> TestTree-testUpdateMLModel = req+requestUpdateMLModel :: UpdateMLModel -> TestTree+requestUpdateMLModel = req     "UpdateMLModel"     "fixture/UpdateMLModel.yaml" -testGetBatchPrediction :: GetBatchPrediction -> TestTree-testGetBatchPrediction = req+requestGetBatchPrediction :: GetBatchPrediction -> TestTree+requestGetBatchPrediction = req     "GetBatchPrediction"     "fixture/GetBatchPrediction.yaml" -testDescribeBatchPredictions :: DescribeBatchPredictions -> TestTree-testDescribeBatchPredictions = req+requestDescribeBatchPredictions :: DescribeBatchPredictions -> TestTree+requestDescribeBatchPredictions = req     "DescribeBatchPredictions"     "fixture/DescribeBatchPredictions.yaml" -testCreateDataSourceFromRDS :: CreateDataSourceFromRDS -> TestTree-testCreateDataSourceFromRDS = req+requestCreateDataSourceFromRDS :: CreateDataSourceFromRDS -> TestTree+requestCreateDataSourceFromRDS = req     "CreateDataSourceFromRDS"     "fixture/CreateDataSourceFromRDS.yaml" -testCreateEvaluation :: CreateEvaluation -> TestTree-testCreateEvaluation = req+requestCreateEvaluation :: CreateEvaluation -> TestTree+requestCreateEvaluation = req     "CreateEvaluation"     "fixture/CreateEvaluation.yaml" -testPredict :: Predict -> TestTree-testPredict = req+requestPredict :: Predict -> TestTree+requestPredict = req     "Predict"     "fixture/Predict.yaml" -testDeleteRealtimeEndpoint :: DeleteRealtimeEndpoint -> TestTree-testDeleteRealtimeEndpoint = req+requestDeleteRealtimeEndpoint :: DeleteRealtimeEndpoint -> TestTree+requestDeleteRealtimeEndpoint = req     "DeleteRealtimeEndpoint"     "fixture/DeleteRealtimeEndpoint.yaml" -testCreateBatchPrediction :: CreateBatchPrediction -> TestTree-testCreateBatchPrediction = req+requestCreateBatchPrediction :: CreateBatchPrediction -> TestTree+requestCreateBatchPrediction = req     "CreateBatchPrediction"     "fixture/CreateBatchPrediction.yaml" -testGetEvaluation :: GetEvaluation -> TestTree-testGetEvaluation = req+requestGetEvaluation :: GetEvaluation -> TestTree+requestGetEvaluation = req     "GetEvaluation"     "fixture/GetEvaluation.yaml" -testDescribeEvaluations :: DescribeEvaluations -> TestTree-testDescribeEvaluations = req+requestDescribeEvaluations :: DescribeEvaluations -> TestTree+requestDescribeEvaluations = req     "DescribeEvaluations"     "fixture/DescribeEvaluations.yaml" -testCreateRealtimeEndpoint :: CreateRealtimeEndpoint -> TestTree-testCreateRealtimeEndpoint = req+requestCreateRealtimeEndpoint :: CreateRealtimeEndpoint -> TestTree+requestCreateRealtimeEndpoint = req     "CreateRealtimeEndpoint"     "fixture/CreateRealtimeEndpoint.yaml" -testDescribeMLModels :: DescribeMLModels -> TestTree-testDescribeMLModels = req+requestDescribeMLModels :: DescribeMLModels -> TestTree+requestDescribeMLModels = req     "DescribeMLModels"     "fixture/DescribeMLModels.yaml" -testDescribeDataSources :: DescribeDataSources -> TestTree-testDescribeDataSources = req+requestDescribeDataSources :: DescribeDataSources -> TestTree+requestDescribeDataSources = req     "DescribeDataSources"     "fixture/DescribeDataSources.yaml"  -- Responses -testUpdateDataSourceResponse :: UpdateDataSourceResponse -> TestTree-testUpdateDataSourceResponse = res+responseUpdateDataSource :: UpdateDataSourceResponse -> TestTree+responseUpdateDataSource = res     "UpdateDataSourceResponse"     "fixture/UpdateDataSourceResponse.proto"     machineLearning     (Proxy :: Proxy UpdateDataSource) -testDeleteDataSourceResponse :: DeleteDataSourceResponse -> TestTree-testDeleteDataSourceResponse = res+responseDeleteDataSource :: DeleteDataSourceResponse -> TestTree+responseDeleteDataSource = res     "DeleteDataSourceResponse"     "fixture/DeleteDataSourceResponse.proto"     machineLearning     (Proxy :: Proxy DeleteDataSource) -testCreateDataSourceFromRedshiftResponse :: CreateDataSourceFromRedshiftResponse -> TestTree-testCreateDataSourceFromRedshiftResponse = res+responseCreateDataSourceFromRedshift :: CreateDataSourceFromRedshiftResponse -> TestTree+responseCreateDataSourceFromRedshift = res     "CreateDataSourceFromRedshiftResponse"     "fixture/CreateDataSourceFromRedshiftResponse.proto"     machineLearning     (Proxy :: Proxy CreateDataSourceFromRedshift) -testCreateDataSourceFromS3Response :: CreateDataSourceFromS3Response -> TestTree-testCreateDataSourceFromS3Response = res+responseCreateDataSourceFromS3 :: CreateDataSourceFromS3Response -> TestTree+responseCreateDataSourceFromS3 = res     "CreateDataSourceFromS3Response"     "fixture/CreateDataSourceFromS3Response.proto"     machineLearning     (Proxy :: Proxy CreateDataSourceFromS3) -testCreateMLModelResponse :: CreateMLModelResponse -> TestTree-testCreateMLModelResponse = res+responseCreateMLModel :: CreateMLModelResponse -> TestTree+responseCreateMLModel = res     "CreateMLModelResponse"     "fixture/CreateMLModelResponse.proto"     machineLearning     (Proxy :: Proxy CreateMLModel) -testDeleteBatchPredictionResponse :: DeleteBatchPredictionResponse -> TestTree-testDeleteBatchPredictionResponse = res+responseDeleteBatchPrediction :: DeleteBatchPredictionResponse -> TestTree+responseDeleteBatchPrediction = res     "DeleteBatchPredictionResponse"     "fixture/DeleteBatchPredictionResponse.proto"     machineLearning     (Proxy :: Proxy DeleteBatchPrediction) -testUpdateBatchPredictionResponse :: UpdateBatchPredictionResponse -> TestTree-testUpdateBatchPredictionResponse = res+responseUpdateBatchPrediction :: UpdateBatchPredictionResponse -> TestTree+responseUpdateBatchPrediction = res     "UpdateBatchPredictionResponse"     "fixture/UpdateBatchPredictionResponse.proto"     machineLearning     (Proxy :: Proxy UpdateBatchPrediction) -testGetMLModelResponse :: GetMLModelResponse -> TestTree-testGetMLModelResponse = res+responseGetMLModel :: GetMLModelResponse -> TestTree+responseGetMLModel = res     "GetMLModelResponse"     "fixture/GetMLModelResponse.proto"     machineLearning     (Proxy :: Proxy GetMLModel) -testGetDataSourceResponse :: GetDataSourceResponse -> TestTree-testGetDataSourceResponse = res+responseGetDataSource :: GetDataSourceResponse -> TestTree+responseGetDataSource = res     "GetDataSourceResponse"     "fixture/GetDataSourceResponse.proto"     machineLearning     (Proxy :: Proxy GetDataSource) -testUpdateEvaluationResponse :: UpdateEvaluationResponse -> TestTree-testUpdateEvaluationResponse = res+responseUpdateEvaluation :: UpdateEvaluationResponse -> TestTree+responseUpdateEvaluation = res     "UpdateEvaluationResponse"     "fixture/UpdateEvaluationResponse.proto"     machineLearning     (Proxy :: Proxy UpdateEvaluation) -testDeleteEvaluationResponse :: DeleteEvaluationResponse -> TestTree-testDeleteEvaluationResponse = res+responseDeleteEvaluation :: DeleteEvaluationResponse -> TestTree+responseDeleteEvaluation = res     "DeleteEvaluationResponse"     "fixture/DeleteEvaluationResponse.proto"     machineLearning     (Proxy :: Proxy DeleteEvaluation) -testDeleteMLModelResponse :: DeleteMLModelResponse -> TestTree-testDeleteMLModelResponse = res+responseDeleteMLModel :: DeleteMLModelResponse -> TestTree+responseDeleteMLModel = res     "DeleteMLModelResponse"     "fixture/DeleteMLModelResponse.proto"     machineLearning     (Proxy :: Proxy DeleteMLModel) -testUpdateMLModelResponse :: UpdateMLModelResponse -> TestTree-testUpdateMLModelResponse = res+responseUpdateMLModel :: UpdateMLModelResponse -> TestTree+responseUpdateMLModel = res     "UpdateMLModelResponse"     "fixture/UpdateMLModelResponse.proto"     machineLearning     (Proxy :: Proxy UpdateMLModel) -testGetBatchPredictionResponse :: GetBatchPredictionResponse -> TestTree-testGetBatchPredictionResponse = res+responseGetBatchPrediction :: GetBatchPredictionResponse -> TestTree+responseGetBatchPrediction = res     "GetBatchPredictionResponse"     "fixture/GetBatchPredictionResponse.proto"     machineLearning     (Proxy :: Proxy GetBatchPrediction) -testDescribeBatchPredictionsResponse :: DescribeBatchPredictionsResponse -> TestTree-testDescribeBatchPredictionsResponse = res+responseDescribeBatchPredictions :: DescribeBatchPredictionsResponse -> TestTree+responseDescribeBatchPredictions = res     "DescribeBatchPredictionsResponse"     "fixture/DescribeBatchPredictionsResponse.proto"     machineLearning     (Proxy :: Proxy DescribeBatchPredictions) -testCreateDataSourceFromRDSResponse :: CreateDataSourceFromRDSResponse -> TestTree-testCreateDataSourceFromRDSResponse = res+responseCreateDataSourceFromRDS :: CreateDataSourceFromRDSResponse -> TestTree+responseCreateDataSourceFromRDS = res     "CreateDataSourceFromRDSResponse"     "fixture/CreateDataSourceFromRDSResponse.proto"     machineLearning     (Proxy :: Proxy CreateDataSourceFromRDS) -testCreateEvaluationResponse :: CreateEvaluationResponse -> TestTree-testCreateEvaluationResponse = res+responseCreateEvaluation :: CreateEvaluationResponse -> TestTree+responseCreateEvaluation = res     "CreateEvaluationResponse"     "fixture/CreateEvaluationResponse.proto"     machineLearning     (Proxy :: Proxy CreateEvaluation) -testPredictResponse :: PredictResponse -> TestTree-testPredictResponse = res+responsePredict :: PredictResponse -> TestTree+responsePredict = res     "PredictResponse"     "fixture/PredictResponse.proto"     machineLearning     (Proxy :: Proxy Predict) -testDeleteRealtimeEndpointResponse :: DeleteRealtimeEndpointResponse -> TestTree-testDeleteRealtimeEndpointResponse = res+responseDeleteRealtimeEndpoint :: DeleteRealtimeEndpointResponse -> TestTree+responseDeleteRealtimeEndpoint = res     "DeleteRealtimeEndpointResponse"     "fixture/DeleteRealtimeEndpointResponse.proto"     machineLearning     (Proxy :: Proxy DeleteRealtimeEndpoint) -testCreateBatchPredictionResponse :: CreateBatchPredictionResponse -> TestTree-testCreateBatchPredictionResponse = res+responseCreateBatchPrediction :: CreateBatchPredictionResponse -> TestTree+responseCreateBatchPrediction = res     "CreateBatchPredictionResponse"     "fixture/CreateBatchPredictionResponse.proto"     machineLearning     (Proxy :: Proxy CreateBatchPrediction) -testGetEvaluationResponse :: GetEvaluationResponse -> TestTree-testGetEvaluationResponse = res+responseGetEvaluation :: GetEvaluationResponse -> TestTree+responseGetEvaluation = res     "GetEvaluationResponse"     "fixture/GetEvaluationResponse.proto"     machineLearning     (Proxy :: Proxy GetEvaluation) -testDescribeEvaluationsResponse :: DescribeEvaluationsResponse -> TestTree-testDescribeEvaluationsResponse = res+responseDescribeEvaluations :: DescribeEvaluationsResponse -> TestTree+responseDescribeEvaluations = res     "DescribeEvaluationsResponse"     "fixture/DescribeEvaluationsResponse.proto"     machineLearning     (Proxy :: Proxy DescribeEvaluations) -testCreateRealtimeEndpointResponse :: CreateRealtimeEndpointResponse -> TestTree-testCreateRealtimeEndpointResponse = res+responseCreateRealtimeEndpoint :: CreateRealtimeEndpointResponse -> TestTree+responseCreateRealtimeEndpoint = res     "CreateRealtimeEndpointResponse"     "fixture/CreateRealtimeEndpointResponse.proto"     machineLearning     (Proxy :: Proxy CreateRealtimeEndpoint) -testDescribeMLModelsResponse :: DescribeMLModelsResponse -> TestTree-testDescribeMLModelsResponse = res+responseDescribeMLModels :: DescribeMLModelsResponse -> TestTree+responseDescribeMLModels = res     "DescribeMLModelsResponse"     "fixture/DescribeMLModelsResponse.proto"     machineLearning     (Proxy :: Proxy DescribeMLModels) -testDescribeDataSourcesResponse :: DescribeDataSourcesResponse -> TestTree-testDescribeDataSourcesResponse = res+responseDescribeDataSources :: DescribeDataSourcesResponse -> TestTree+responseDescribeDataSources = res     "DescribeDataSourcesResponse"     "fixture/DescribeDataSourcesResponse.proto"     machineLearning