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FastPCA is a fast, distributed, pure C, iterative PCA ( Principal Component Analysis) implementation (according to Roweis' PPCA) by Ville Tuulos. It is aimed specially for very large co-occurrence matrices encountered in the field of Information Retrieval. FastPCA is released under the Gnu General Public Lisence.

Download current version: fastpca290903.tar.gz


MPCA is a comprehensive suite of tools for doing discrete principal components analysis on data sets of size 100Mb or more. Scaling is done using sparse vectors, multi-threading, memory mapping, and other POSIX tricks. Reports, file dumping utilities, and other utilities are included. The general problem of discrete components analysis is variously called grade of membership, PLSA, non-neg.matrix factorization, multinomial admixtures, LDA, and multinomial PCA. Further information and downloads at