github catboost/catboost v0.5
Release 0.5

Major Features And Improvements

  • In Python we added a new method eval_metrics: now it's possible for a given model to calculate specified metric values for each iteration on specified dataset.
  • One command-line binary for CPU and GPU: in CatBoost you can switch between CPU and GPU training by changing single parameter value task-type CPU or GPU (task_type 'CPU', 'GPU' in python bindings). Windows build still contains two binaries.
  • We have speed up the training up to 30% for datasets with a lot of objects.
  • Up to 10% speed-up of GPU implementation on Pascal cards

Breaking Changes

Cmdline:

  • Training parameter gradient-iterations renamed to leaf-estimation-iterations.
  • border option removed. If you want to specify border for binary classification mode you need to specify it in the following way: loss-function Logloss:Border=0.5
  • CTR parameters are changed:
    • Removed priors, per-feature-priors, ctr-binarization;
    • Added simple-ctr, combintations-ctr, per-feature-ctr;
      More details will be published in our documentation.

Python and R:

  • Training parameter gradient_iterations renamed to leaf_estimation_iterations.
  • border option removed. If you want to specify border for binary classification mode you need to specify it in the following way: loss_function='Logloss:Border=0.5'
  • CTR parameters are changed:
    • Removed priors, per_feature_priors, ctr_binarization;
    • Added simple_ctr, combintations_ctr, per_feature_ctr;
      More details will be published in our documentation.

Bug Fixes and Other Changes

  • Stability improvements and bug fixes

As usual we are grateful to all who filed issues, asked and answered questions.

latest releases: v1.0.0, v0.26.1, v0.26...
3 years ago