145554613376103 ## External Models ## CatBoost catboost / catboost Unwatch 167 ★ Unstar 3,033 Fork 399 << Code ① Issues 77 Pull requests 2 Insights ☀ Settings CatBoost is an open-source gradient on decision trees library with categorical features support out of the box for Python, R https://catboost.yandex Edit machine-learning decision-trees gradient-boosting gbm gödt python kaggle > Best solution for heterogeneous data > Works well for small data > Easy to use ## CatBoost advantages Good quality for default parameters > Sophisticated categorical features support

145554613376103 ## External Models ## CatBoost catboost / catboost Unwatch 167 ★ Unstar 3,033 Fork 399 << Code ① Issues 77 Pull requests 2 Insights ☀ Settings CatBoost is an open-source gradient on decision trees library with categorical features support out of the box for Python, R https://catboost.yandex Edit machine-learning decision-trees gradient-boosting gbm gödt python kaggle > Best solution for heterogeneous data > Works well for small data > Easy to use ## CatBoost advantages Good quality for default parameters > Sophisticated categorical features support

[Image](/uploads/documents/7/d/3/1/7d311727aa3044d8ea399effbf9be0c5/p5_3.jpg) ## Yandex CatBoost clf = catboost.CatBoostClassifier(n_estimators=100, learning_rate=1.0) clf.fit(data, labels) predictions

|1|Gradient Boosting Regressor|2671.5927|23019681.2661|4794.6037|0.8393|0.4439|0.3143|0.0683| |2|CatBoost Regressor|2814.6048|24757340.4659|4973.7765|0.8265|0.4734|0.3427|1.1286| |3|Random Forest|2779.2026|25351757