datasets: Classical data sets for statistics and machine learning

[ data, data-mining, library, machine-learning, mit, statistics ] [ Propose Tags ]

Classical machine learning and statistics datasets from the UCI Machine Learning Repository and other sources.

The datasets package defines two different kinds of datasets:

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)
Versions 0.1.0,, 0.2,,,, 0.2.1, 0.2.2, 0.2.3, 0.2.4, 0.2.5, 0.3.0
Change log
Dependencies aeson, attoparsec (>=0.13), base (>=4.6 && <5), bytestring, cassava, data-default-class, directory, file-embed, filepath, hashable, microlens, req (>=1.0.0), stringsearch, text, time, vector [details]
License MIT
Author Tom Nielsen <>
Maintainer Marco Zocca <ocramz fripost org>
Category Statistics, Machine Learning, Data Mining, Data
Home page
Bug tracker
Source repo head: git clone
Uploaded by ocramz at Mon Dec 31 14:42:11 UTC 2018
Distributions NixOS:0.3.0
Downloads 2693 total (125 in the last 30 days)
Rating 2.0 (votes: 1) [estimated by rule of succession]
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Status Hackage Matrix CI
Docs available [build log]
Last success reported on 2018-12-31 [all 1 reports]


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