Cabal revisions of datasets-0.2
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revision 1
-Name: datasets-Version: 0.2-Synopsis: Classical data sets for statistics and machine learning-Description: Classical machine learning and statistics datasets from- the UCI Machine Learning Repository and other sources.- .- The datasets package defines two different kinds of datasets:- .- * small data sets which are directly (or indirectly with `file-embed`)- embedded in the package as pure values and do not require network or IO to download- the data set. This includes Iris, Anscombe and OldFaithful.- .- * other data sets which need to be fetched over the network with- `Numeric.Datasets.getDataset` and are cached in a local temporary directory.- .- > import Numeric.Datasets (getDataset)- > import Numeric.Datasets.Iris (iris)- > import Numeric.Datasets.Abalone (abalone)- >- > main = do- > -- The Iris data set is embedded- > print (length iris)- > print (head iris)- > -- The Abalone dataset is fetched- > abas <- getDataset abalone- > print (length abas)- > print (head abas)--License: MIT-License-file: LICENSE-Author: Tom Nielsen <tanielsen@gmail.com>-Maintainer: Tom Nielsen <tanielsen@gmail.com>-build-type: Simple-Cabal-Version: >= 1.8-homepage: https://github.com/glutamate/datasets-bug-reports: https://github.com/glutamate/datasets/issues-category: Statistics, Machine Learning, Data Mining, Data--source-repository head- type: git- location: https://github.com/glutamate/datasets---Library- ghc-options: -Wall- hs-source-dirs: src-- Exposed-modules:- Numeric.Datasets- , Numeric.Datasets.Anscombe- , Numeric.Datasets.BostonHousing- , Numeric.Datasets.OldFaithful- , Numeric.Datasets.Abalone- , Numeric.Datasets.Adult- , Numeric.Datasets.BreastCancerWisconsin- , Numeric.Datasets.Car- , Numeric.Datasets.Iris- , Numeric.Datasets.Michelson- , Numeric.Datasets.Nightingale- , Numeric.Datasets.Wine- Build-depends:- base >= 4.6 && < 5- , cassava- , HTTP- , hashable- , filepath- , bytestring- , directory- , vector- , text- , stringsearch- , file-embed- , aeson- , time+Name: datasets +Version: 0.2 +x-revision: 1 +Synopsis: Classical data sets for statistics and machine learning +Description: Classical machine learning and statistics datasets from + the UCI Machine Learning Repository and other sources. + . + The datasets package defines two different kinds of datasets: + . + * small data sets which are directly (or indirectly with `file-embed`) + embedded in the package as pure values and do not require network or IO to download + the data set. This includes Iris, Anscombe and OldFaithful. + . + * other data sets which need to be fetched over the network with + `Numeric.Datasets.getDataset` and are cached in a local temporary directory. + . + > import Numeric.Datasets (getDataset) + > import Numeric.Datasets.Iris (iris) + > import Numeric.Datasets.Abalone (abalone) + > + > main = do + > -- The Iris data set is embedded + > print (length iris) + > print (head iris) + > -- The Abalone dataset is fetched + > abas <- getDataset abalone + > print (length abas) + > print (head abas) + +License: MIT +License-file: LICENSE +Author: Tom Nielsen <tanielsen@gmail.com> +Maintainer: Tom Nielsen <tanielsen@gmail.com> +build-type: Simple +Cabal-Version: >= 1.8 +homepage: https://github.com/glutamate/datasets +bug-reports: https://github.com/glutamate/datasets/issues +category: Statistics, Machine Learning, Data Mining, Data + +source-repository head + type: git + location: https://github.com/glutamate/datasets + + +Library + -- broken release, see https://github.com/glutamate/datasets/issues/2 + build-depends: base<0 + + ghc-options: -Wall + hs-source-dirs: src + + Exposed-modules: + Numeric.Datasets + , Numeric.Datasets.Anscombe + , Numeric.Datasets.BostonHousing + , Numeric.Datasets.OldFaithful + , Numeric.Datasets.Abalone + , Numeric.Datasets.Adult + , Numeric.Datasets.BreastCancerWisconsin + , Numeric.Datasets.Car + , Numeric.Datasets.Iris + , Numeric.Datasets.Michelson + , Numeric.Datasets.Nightingale + , Numeric.Datasets.Wine + Build-depends: + base >= 4.6 && < 5 + , cassava + , HTTP + , hashable + , filepath + , bytestring + , directory + , vector + , text + , stringsearch + , file-embed + , aeson + , time