Matlab package for PCA for datasets with missing values

The Matlab toolbox contains variants of probabilistic models for principal component analysis (PCA) in the presence of missing values. We also implemented unregularized approaches including least-squares and imputation algorithm. Some of the implemented algorithms work for huge datasets such as the Netflix data. The core computations are implemented in C++ with the possibility to use multiple processors.

Implemented algorithms:

• Least-sqaures approach
• Imputation algorithm
• Probabilistic PCA (PPCA)
• Variational Bayesian PCA (VBPCA)
• PPCA and VBPCA with simplified posterior

See our technical report explaining the math. Download the package.