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Cabal revisions of HLearn-distributions-1.1.0.2

Hackage metadata revisions edit the .cabal file after upload; each diff below is one revision.

revision 1
-Name:                HLearn-distributions-Version:             1.1.0.2-Synopsis:            Distributions for use with the HLearn library-Description:         This module is used to estimate statistical distributions from data.  It is based on the algebraic properties of the "HomTrainer" type class from the HLearn-algebra package.-Category:            Data Mining, Machine Learning, Statistics-License:             BSD3---License-file:        LICENSE-Author:              Mike izbicki-Maintainer:          mike@izbicki.me-Build-Type:          Simple-Cabal-Version:       >=1.8-homepage:            http://github.com/mikeizbicki/HLearn/-bug-reports:         http://github.com/mikeizbicki/HLearn/issues--Library-    Build-Depends:      -        HLearn-algebra          >= 1.0.0.1,-        HLearn-datastructures   >= 1.1,-        ConstraintKinds         >= 0.0.1,-        base                    >= 3 && < 5,-        -        template-haskell,-        deepseq                 >= 1.3.0.1,-        list-extras             >= 0.4.1,-        containers              >= 0.5,-        statistics              >= 0.10.2,-        -        QuickCheck              >= 2.5.1,-        vector                  >= 0.9,-        vector-th-unbox         >= 0.2,-        graphviz                >= 2999.16,-        hmatrix                 >= 0.14,-        gamma                   >= 0.9.0.2,        -        erf                     >= 2.0.0.0,--        -- are these really necessary?-        array                   >= 0.4.0,-        process                 >= 1.1.0.2,-        MonadRandom             >= 0.1.6,-        math-functions          >= 0.1.1,-        normaldistribution      >= 1.1.0--        -    hs-source-dirs:     src-    ghc-options:        -        -rtsopts -        -- -auto-all -        -- -caf-all -        -funbox-strict-fields-        -O2 -        -- -fllvm-    Exposed-modules:-        HLearn.Models.Distributions-        HLearn.Models.Distributions.Common-        HLearn.Models.Distributions.Kernels-        HLearn.Models.Distributions.Visualization.Gnuplot-        HLearn.Models.Distributions.Visualization.Graphviz-        HLearn.Models.Distributions.Univariate.Binomial-        HLearn.Models.Distributions.Univariate.Categorical-        HLearn.Models.Distributions.Univariate.Exponential-        HLearn.Models.Distributions.Univariate.Geometric-        HLearn.Models.Distributions.Univariate.KernelDensityEstimator-        HLearn.Models.Distributions.Univariate.LogNormal-        HLearn.Models.Distributions.Univariate.Normal-        HLearn.Models.Distributions.Univariate.Poisson-        --HLearn.Models.Distributions.Univariate.Uniform-        HLearn.Models.Distributions.Univariate.Internal.MissingData-        HLearn.Models.Distributions.Univariate.Internal.Moments-        HLearn.Models.Distributions.Multivariate.Interface-        HLearn.Models.Distributions.Multivariate.MultiNormal-        HLearn.Models.Distributions.Multivariate.Internal.CatContainer-        HLearn.Models.Distributions.Multivariate.Internal.Container-        HLearn.Models.Distributions.Multivariate.Internal.Ignore-        HLearn.Models.Distributions.Multivariate.Internal.Marginalization-        HLearn.Models.Distributions.Multivariate.Internal.TypeLens-        HLearn.Models.Distributions.Multivariate.Internal.Unital--    Extensions:-        FlexibleInstances-        FlexibleContexts-        MultiParamTypeClasses-        FunctionalDependencies-        UndecidableInstances-        ScopedTypeVariables-        BangPatterns-        TypeOperators-        GeneralizedNewtypeDeriving-        --DataKinds-        TypeFamilies-        --PolyKinds-        StandaloneDeriving-        GADTs-        KindSignatures-+Name:                HLearn-distributions
+Version:             1.1.0.2
+x-revision: 1
+Synopsis:            Distributions for use with the HLearn library
+Description:         
+    This package is deprecated.  The latest version of HLearn is available from the github repo at: <http://github.com/mikeizbicki/hlearn>.  If you want to use HLearn, I strongly recommend you contact me (mike@izbicki.me) first to see if HLearn will really fit your needs.
+Category:            Data Mining, Machine Learning, Statistics
+License:             BSD3
+--License-file:        LICENSE
+Author:              Mike izbicki
+Maintainer:          mike@izbicki.me
+Build-Type:          Simple
+Cabal-Version:       >=1.8
+homepage:            http://github.com/mikeizbicki/HLearn/
+bug-reports:         http://github.com/mikeizbicki/HLearn/issues
+
+Library
+    Build-Depends:      
+        HLearn-algebra          >= 1.0.0.1,
+        HLearn-datastructures   >= 1.1,
+        ConstraintKinds         >= 0.0.1,
+        base                    >= 3 && < 5,
+        
+        template-haskell,
+        deepseq                 >= 1.3.0.1,
+        list-extras             >= 0.4.1,
+        containers              >= 0.5,
+        statistics              >= 0.10.2,
+        
+        QuickCheck              >= 2.5.1,
+        vector                  >= 0.9,
+        vector-th-unbox         >= 0.2,
+        graphviz                >= 2999.16,
+        hmatrix                 >= 0.14,
+        gamma                   >= 0.9.0.2,        
+        erf                     >= 2.0.0.0,
+
+        -- are these really necessary?
+        array                   >= 0.4.0,
+        process                 >= 1.1.0.2,
+        MonadRandom             >= 0.1.6,
+        math-functions          >= 0.1.1,
+        normaldistribution      >= 1.1.0
+
+        
+    hs-source-dirs:     src
+    ghc-options:        
+        -rtsopts 
+        -- -auto-all 
+        -- -caf-all 
+        -funbox-strict-fields
+        -O2 
+        -- -fllvm
+    Exposed-modules:
+        HLearn.Models.Distributions
+        HLearn.Models.Distributions.Common
+        HLearn.Models.Distributions.Kernels
+        HLearn.Models.Distributions.Visualization.Gnuplot
+        HLearn.Models.Distributions.Visualization.Graphviz
+        HLearn.Models.Distributions.Univariate.Binomial
+        HLearn.Models.Distributions.Univariate.Categorical
+        HLearn.Models.Distributions.Univariate.Exponential
+        HLearn.Models.Distributions.Univariate.Geometric
+        HLearn.Models.Distributions.Univariate.KernelDensityEstimator
+        HLearn.Models.Distributions.Univariate.LogNormal
+        HLearn.Models.Distributions.Univariate.Normal
+        HLearn.Models.Distributions.Univariate.Poisson
+        --HLearn.Models.Distributions.Univariate.Uniform
+        HLearn.Models.Distributions.Univariate.Internal.MissingData
+        HLearn.Models.Distributions.Univariate.Internal.Moments
+        HLearn.Models.Distributions.Multivariate.Interface
+        HLearn.Models.Distributions.Multivariate.MultiNormal
+        HLearn.Models.Distributions.Multivariate.Internal.CatContainer
+        HLearn.Models.Distributions.Multivariate.Internal.Container
+        HLearn.Models.Distributions.Multivariate.Internal.Ignore
+        HLearn.Models.Distributions.Multivariate.Internal.Marginalization
+        HLearn.Models.Distributions.Multivariate.Internal.TypeLens
+        HLearn.Models.Distributions.Multivariate.Internal.Unital
+
+    Extensions:
+        FlexibleInstances
+        FlexibleContexts
+        MultiParamTypeClasses
+        FunctionalDependencies
+        UndecidableInstances
+        ScopedTypeVariables
+        BangPatterns
+        TypeOperators
+        GeneralizedNewtypeDeriving
+        --DataKinds
+        TypeFamilies
+        --PolyKinds
+        StandaloneDeriving
+        GADTs
+        KindSignatures
+