The `get_feature_importance` method is a function provided by the `catboost.CatBoostClassifier` class in the Python CatBoost library. It is used to retrieve the importance of each feature in a trained CatBoost classifier model. The feature importance is calculated based on the impact each feature has on the model's predictions. This method returns a list of feature importances, where each value corresponds to a specific feature in the dataset. The higher the importance value, the more influential the feature is in making accurate predictions with the model. By examining the feature importances, users can gain insights into which features have the most significant impact on the model's performance.
Python CatBoostClassifier.get_feature_importance - 33 examples found. These are the top rated real world Python examples of catboost.CatBoostClassifier.get_feature_importance extracted from open source projects. You can rate examples to help us improve the quality of examples.