catboost 0.16.1

v0.16.1

on Python PyPI

Breaking changes:

• parameter fold_count is now called cv in grid_search() and randomized_search
• cv results are now returned from grid_search() and randomized_search() in res['cv_results'] field

New features:

• R-language function catboost.save_model() now supports PMML, ONNX and other formats
• Parameter monotone_constraints in python API allows specifying numerical features that the prediction shall depend on monotonically

Bug fixes:

• Fixed eval_metric calculation for training with weights (in release 0.16 evaluation of a metric that was equal to an optimized loss did not use weights by default, so overfitting detector worked incorrectly)

Improvements:

• Added option verbose to grid_search() and randomized_search()
• Added tutorial on grid_search() and randomized_search()