Learning: The most frequently used machine learning tools

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Versions [RSS] 0.0.0, 0.0.1, 0.0.2, 0.0.3, 0.1.0
Change log ChangeLog.md
Dependencies base (>=4.7 && <5), containers, hmatrix (>=0.18.0.0), Learning, vector [details]
License BSD-3-Clause
Copyright Bogdan Penkovsky
Author Bogdan Penkovsky
Maintainer dev at penkovsky [dot] com
Category Machine Learning
Home page https://github.com/masterdezign/Learning#readme
Bug tracker https://github.com/masterdezign/Learning/issues
Source repo head: git clone https://github.com/masterdezign/Learning
Uploaded by penkovsky at 2018-02-15T16:20:57Z
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Reverse Dependencies 1 direct, 0 indirect [details]
Executables learning-pca-advanced, learning-pca
Downloads 2871 total (17 in the last 30 days)
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Status Docs not available [build log]
All reported builds failed as of 2018-02-16 [all 3 reports]

Readme for Learning-0.0.2

[back to package description]

Learning

A Haskell micro library containing the most common machine learning tools.

The name of the package can be interpreted in two ways:

  1. Either as "Learning" in "Machine Learning".
  2. Or "Learning" meaning that examples are written in literate style and can be used to discover machine learning techniques.

Features

  • Supervised learning
    • Ridge regression
    • Linear classifier
  • Evaluation metrics
  • Principal components analysis

Getting Started

Use Stack.

 $ git clone https://github.com/masterdezign/Learning.git && cd Learning
 $ stack build --install-ghc

Demo 1: principal components analysis (PCA)

Launch the PCA demo

 $ stack exec learning-pca

Demo 2: advanced principal components analysis (PCA)

Launch the advanced PCA demo

 $ stack exec learning-pca-advanced

What's next?

Check the documentation or open an issue.