Python Dimension Reduction Library

The repo contains some libraries below:

1. A self-customized unsupervised dimension reduction algorithm, Principal Component Analysis(PCA) and two supervised dimension reduction algorithms, Linear Discriminant Analysis(LDA) and Discriminant Component Analysis(DCA).
2. Two Differentially Private PCA algorithm implementation, regarding the paper Analyze gauss: optimal bounds for privacy-preserving principal component analysis and Private approximations of the 2nd-moment matrix using existing techniques in linear regression.
3. A implementation of Differentially Private Distributed PCA.

There are also some ongoing experiments code inside.