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Introduction

This is a Java library that provides some algorithms to efficiently perform principal component analysis.

Downloads

The library can be downloaded as a binary or source package from https://github.com/trickl/trickl-pca/downloads.

The source can be also retrieved straight from the Git repository: git clone git@github.com:trickl/trickl-pca.git.

Features

HallMarshallMartin - An incremental algorithm described by a paper by Hall, Marshall and Martin. Modified beyond the scope of that paper to work efficienttly on sparse matrices. SVDPCA - A standard batch algorithm for PCA that requires a Singular Value Decomposition solver. SkocajLeonardis - An incremental algorithm that allows each input to have a temporal weight, based on a paper by Skocaj and Leonardis.

Requirements

Depends on the Colt matrix library.

License and conditions of use

The program is available under GNU General Public License (see file license-gpl.txt in the distribution package for the text of the license).

Example usage

Some Junit tests are provided and should be used to consult usage.

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Contains sparse, incremental algorithms for principal component analysis.

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