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Delayed sparse matrix in Python

Project description

Delayed Sparse Matrix

Efficient sparse matrix implementation for various "Principal Component Analysis". And demo usages of the efficient implementation for Correspondence Analysis(CA) and principal component analysis (PCA).

To compare with existing methods, you can execute #+BEGIN_SRC bash bash #+END_SRC

This library is effective when the input matrix size ls large. But, in order to demonstrations, the demo programs use only a small matrix. You can test more large matrix by setting SIZE variable in demo-*.sh

When the input matrix size is large, the program of this library will finish within in few minutes, but the existing methods take hours.

You can find more general description about CA and PCA in


>>> pip3 install sklearn

In order to execute, you need install /usr/bin/time and orange library

>>> apt-get install time
>>> pip3 install orange


Author: Hirotaka Niitsuma.

@2018 Hirotaka Niirtsuma.

You can use these codes olny for self evaluation. Cannot use these codes for commercial and academical use.

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