Laboratory of Computer and Information Science / Neural Networks Research Centre CIS Lab Helsinki University of Technology

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:

See our JMLR paper explaining the math. Download the package.

You are at: CIS → Software by Alexander Ilin

Page maintained by webmaster at, last updated Friday, 09-May-2014 09:47:46 EEST