You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
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