py_predpurchase.function_feature_importance

Module Contents

Functions

get_feature_importances(model, X_columns)

Fits the model, extracts feature importances, sorts them, and returns them as a DataFrame.

py_predpurchase.function_feature_importance.get_feature_importances(model, X_columns)

Fits the model, extracts feature importances, sorts them, and returns them as a DataFrame.

Parameters:

• model: The trained machine learning model with a feature_importances_ attribute.

• X_columns: The column names of the features in entered dataset.

Returns:

pandas.DataFrame - DataFrame:

• 1 column containing the feature importances sorted in descending order.

• index of DataFrame has feature names

Examples:

• Assuming:

  • random_forest is your RandomForestClassifier instance

  • X_train.columns is your feature names

  >>> feature_importances_df = get_feature_importances(random_forest, X_train.columns)
  

Notes:

This function uses the pandas library produce the results as a pandas DataFrame.