- sklearn_evaluation.table.feature_importances(data, top_n=None, feature_names=None)#
Get and order feature importances from a scikit-learn model or from an array-like structure.
If data is a scikit-learn model with sub-estimators (e.g. RandomForest, AdaBoost) the function will compute the standard deviation of each feature.
data (sklearn model or array-like structure) – Object to get the data from.
top_n (int) – Only get results for the top_n features.
feature_names (array-like) – Feature_names
Table object with the data. Columns are feature_name, importance (std_ only included for models with sub-estimators)
- Return type: