Extracting LightGBM Feature Importance

This function calculates the feature importance from a LightGBM model and returns a DataFrame with the importance scores.

Technology Stack : pandas, lightgbm

Code Type : Function

Code Difficulty : Intermediate

                
                    
def random_lightgbm_feature_importance(df, target_column, model):
    """
    This function calculates the feature importance from a LightGBM model and returns a DataFrame with the importance scores.

    :param df: pandas DataFrame containing the features and the target variable.
    :param target_column: string, the name of the target variable column.
    :param model: trained LightGBM model.
    :return: pandas DataFrame with feature importance scores.
    """
    import pandas as pd
    from lightgbm import train, LGBMRegressor

    # Extract feature names from the DataFrame
    feature_names = [col for col in df.columns if col != target_column]

    # Get feature importance from the model
    importance = model.feature_importances_

    # Create a DataFrame with feature importance
    feature_importance_df = pd.DataFrame({'Feature': feature_names, 'Importance': importance})

    return feature_importance_df