Cabal revisions of datasets-0.3.0
Hackage metadata revisions edit the .cabal file after upload; each diff below is one revision.
revision 1
-Name: datasets-Version: 0.3.0-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.- .- The @datafiles/@ directory of this package includes copies of a few famous datasets, such as Titanic, Nightingale and Michelson.- .- Example :- .- > 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: Marco Zocca <ocramz fripost org>-build-type: Simple-Cabal-Version: >= 1.10-homepage: https://github.com/DataHaskell/dh-core-bug-reports: https://github.com/DataHaskell/dh-core/issues-category: Statistics, Machine Learning, Data Mining, Data-Tested-With: GHC == 7.10.2, GHC == 7.10.3, GHC == 8.0.1, GHC == 8.4.3-extra-source-files:- changelog.md- datafiles/iris.data- datafiles/michelson.json- datafiles/nightingale.json- datafiles/titanic2_full.tsv- datafiles/netflix/training/mv_0000001.txt- datafiles/netflix/test/qualifying.txt- datafiles/netflix/movies/movie_titles.txt--source-repository head- type: git- location: https://github.com/DataHaskell/dh-core/datasets--Library- ghc-options: -Wall -fno-warn-unused-imports- hs-source-dirs: src- other-extensions: TemplateHaskell- default-language: Haskell2010-- 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.Coal- , Numeric.Datasets.CO2- , Numeric.Datasets.Gapminder- , Numeric.Datasets.Iris- , Numeric.Datasets.Michelson- , Numeric.Datasets.Mushroom - , Numeric.Datasets.Nightingale- , Numeric.Datasets.Quakes- , Numeric.Datasets.States- , Numeric.Datasets.Sunspots- , Numeric.Datasets.Titanic - , Numeric.Datasets.UN- , Numeric.Datasets.Vocabulary- , Numeric.Datasets.Wine- , Numeric.Datasets.WineQuality- , Numeric.Datasets.Netflix- Build-depends:- base >= 4.6 && < 5- , aeson- , attoparsec >= 0.13- , bytestring- , cassava- , data-default-class- , directory- , file-embed- , filepath- , hashable- , microlens- , req >= 1.0.0- , stringsearch- , text- , time- , vector- -- , wreq+Name: datasets +Version: 0.3.0 +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. + . + The @datafiles/@ directory of this package includes copies of a few famous datasets, such as Titanic, Nightingale and Michelson. + . + Example : + . + > 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: Marco Zocca <ocramz fripost org> +build-type: Simple +Cabal-Version: >= 1.10 +homepage: https://github.com/DataHaskell/dh-core +bug-reports: https://github.com/DataHaskell/dh-core/issues +category: Statistics, Machine Learning, Data Mining, Data +Tested-With: GHC == 7.10.2, GHC == 7.10.3, GHC == 8.0.1, GHC == 8.4.3 +extra-source-files: + changelog.md + datafiles/iris.data + datafiles/michelson.json + datafiles/nightingale.json + datafiles/titanic2_full.tsv + datafiles/netflix/training/mv_0000001.txt + datafiles/netflix/test/qualifying.txt + datafiles/netflix/movies/movie_titles.txt + +source-repository head + type: git + location: https://github.com/DataHaskell/dh-core/datasets + +Library + ghc-options: -Wall -fno-warn-unused-imports + hs-source-dirs: src + other-extensions: TemplateHaskell + default-language: Haskell2010 + + 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.Coal + , Numeric.Datasets.CO2 + , Numeric.Datasets.Gapminder + , Numeric.Datasets.Iris + , Numeric.Datasets.Michelson + , Numeric.Datasets.Mushroom + , Numeric.Datasets.Nightingale + , Numeric.Datasets.Quakes + , Numeric.Datasets.States + , Numeric.Datasets.Sunspots + , Numeric.Datasets.Titanic + , Numeric.Datasets.UN + , Numeric.Datasets.Vocabulary + , Numeric.Datasets.Wine + , Numeric.Datasets.WineQuality + , Numeric.Datasets.Netflix + Build-depends: + base >= 4.6 && < 5 + , aeson + , attoparsec >= 0.13 + , bytestring + , cassava + , data-default-class + , directory + , file-embed + , filepath + , hashable + , microlens + , req >= 1.0.0 && < 2 + , stringsearch + , text + , time + , vector + -- , wreq