ReBATE 0.2

• Added documentation with mkdocs.

• Added unit testing. Adopted Travis CI

• Added 'MultiSURF' algorithm, previously only available in scikit-rebate.

• Updated ReBATE to include other updates made to scikit-rebate.

• Fixed score normalizations so they fall between -1 and 1 for all algorithms Now matches scikit-rebate.

• Consolidated MultiSURF* so that one script is used for both multiclass, and other types of endpoints.

• Added an automatic (standard deviation based) ramp function method that is utilized by all algorithms on data with a mix of discrete and continuous features. Taken from scikit-rebate.

• Included steps to support operation of ReBATE in Windows.

• Beyond what was previously used for testing scikit-rebate, we added the 6-bit multiplexer as a test problem as well as a simple 3-class (multiclass) GWAS-style simulated dataset (with 100% heritability).

ReBATE 0.1

• Initial release of Relief algorithms, including ReliefF, SURF, SURF*, MultSURF*, and TuRF.