github catboost/catboost v0.26
0.26

New features

  • #972. Add model evaluation on GPU. Thanks to @rakalexandra.
  • Support Langevin on GPU
  • Save class labels to models in cross validation
  • #1524. Return models after CV. Thanks to @vklyukin
  • [Python] #766. Add CatBoostRanker & pool.get_group_id_hash() for ranking. Thanks to @AnnaAraslanova
  • #262. Make CatBoost widget work in jupyter lab. Thanks to @Dm17r1y
  • [GPU only] Allow to add exponent to score aggregation function
  • Allow to specify threshold parameter for binary classification model. Thanks to @Keksozavr.
  • [C Model API] #503. Allow to specify prediction type.
  • [C Model API] #1201. Get predictions for a specific class.

Breaking changes

  • #1628. Use CUDA 11 by default. CatBoost GPU now requires Linux x86_64 Driver Version >= 450.51.06 Windows x86_64 Driver Version >= 451.82.

Losses and metrics

  • Add MRR and ERR metrics on CPU.
  • Add LambdaMart loss.
  • #1557. Add survivalAFT base logic. Thanks to @blatr.
  • #1286. Add Cox Proportional Hazards Loss. Thanks to @fibersel.
  • #1595. Provide object-oriented interface for setting up metric parameters. Thanks to @ks-korovina.
  • Change default YetiRank decay to 0.85 for better quality.

Python package

  • #1372. Custom logging stream in python package. Thanks to @DianaArapova.
  • #1304. Callback after iteration functionality. Thanks to @qoter.

R package

  • #251. Train parameter synonyms. Thanks to @ebalukova.
  • #252. Add eval_metrics. Thanks to @ebalukova.

Speedups

  • [Python] Speed up custom metrics and objectives with numba (if available)
  • [Python] #1710. Large speedup for cv dataset splitting by sklearn splitter

Other

  • Use Exact leaves estimation method as default on GPU
  • [Spark] #1632. Update version of Scala 2.11 for security reasons.
  • [Python] #1695. Explicitly specify WHEEL 'Root-Is-Purelib' value

Bugfixes

  • Fix default projection dimension for embeddings
  • Fix use_weights for some eval_metrics on GPU - use_weights=False is always respected now
  • [Spark] #1649. The earlyStoppingRounds parameter is not recognized
  • [Spark] #1650. Error when using the autoClassWeights parameter
  • [Spark] #1651. Error about "Auto-stop PValue" when using odType "Iter" and odWait
  • Fix usage of pairlogit weights for CPU fallback metrics when training on GPU
latest releases: v1.0.0, v0.26.1
4 months ago