EpistasisLab/ReBATE

This package includes stand-alone Python code to run any of the included/available Relief-Based algorithms (RBAs) designed for feature weighting/selection as part of a machine learning pipeline (supervised learning). Presently this includes the following core RBAs: ReliefF, SURF, SURF*, and MultiSURF*. Additionally, an implementation of the iterative TuRF mechanism is included. It is still under active development and we encourage you to check back on this repository regularly for updates. These algorithms offer a computationally efficient way to perform feature selection that is sensitive to feature interactions as well as simple univariate associations, unlike most currently available filter-based feature selection methods.