catboost/catboost v0.16.2

on GitHub

Breaking changes:

• Removed get_group_id() and get_features() methods of Pool class

New model analysis tools:

• Added PredictionDiff type of get_feature_importance() method, which is a new method for model analysis. The method shows how the features influenced the fact that among two samples one has a higher prediction. It allows to debug ranking models: you find a pair of samples ranked incorrectly and you look at what features have caused that.
• Added plot_predictions() method

New features:

• model.set_feature_names() method in Python
• Added stratified split to parameter search methods
• Support catboost.load_model() from CPU snapshots for numerical-only datasets
• CatBoostClassifier.score() now supports y as DataFrame
• Added sampling_frequency, per_float_feature_binarization, monotone_constraints parameters to CatBoostClassifier and CatBoostRegresssor

Speedups:

• 2x speedup of multi-classification mode

Bugfixes:

• Fixed score() for multiclassification, #924
• Fixed get_all_params() function, #926

Other improvements:

• Clear error messages when a model cannot be saved