sklearn-sfa 0.1.1

A scikit-learn compatible implementation of Slow Feature Analysis

sklearn-sfa or sksfa is an implementation of Slow Feature Analysis for scikit-learn.

It is meant as a standalone transformer for dimensionality reduction or as a building block for more complex representation learning pipelines utilizing scikit-learn’s extensive collection of machine learning methods.

The package contains a solver for linear SFA and some auxiliary functions. The documentation provides an explanation of the algorithm, different use-cases, as well as pointers how to fully utilize SFA’s potential, e.g., by employing non-linear basis functions or more sophisticated architectures.