sklearn_evaluation.table

feature_importances

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.

Parameters:

• 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

Returns:

Table object with the data. Columns are feature_name, importance (std_ only included for models with sub-estimators)

Return type:

table