Version 0.2#

This release is a major release, with many new features and improvements. For instance, we have added a new implementation of the extended isolation forest, enabled all decision trees to take advantage of partial_fit meaning trees have streaming capabilities. Moreover, we have added an analogous implementation of extra-trees for oblique-trees. Finally, this release includes a highly experimental feature for multivariate high-dimensional hypothesis testing using permutation forests and a feature importance testing forest.

Changelog#

  • Efficiency Upgraded build process to rely on Cython 3.0+, by Adam Li (#109)

  • Feature Allow decision trees to take advantage of partial_fit and monotonic_cst when available, by Adam Li (#109)

  • Feature Implementation of ExtraObliqueDecisionTreeClassifier, ExtraObliqueDecisionTreeRegressor by SUKI-O (#75)

  • Efficiency Around 1.5-2x speed improvement for unsupervised forests, by Adam Li (#114)

  • API Change Allow sqrt and log2 keywords to be used for min_samples_split parameter in unsupervised forests, by Adam Li (#114)

  • Feature Implement extended isolation forest, by Adam Li (#101)

  • Feature Implementation of StreamDecisionForest, by Haoyin Xu and Adam Li (#116)

  • Feature Implementation of Permutation forests and a feature importance testing forest, by Haoyin Xu, Adam Li, Sambit Panda (#125)

Code and Documentation Contributors#

Thanks to everyone who has contributed to the maintenance and improvement of the project since version inception, including: