462d31c615671a48dcac9d77e6de1bc360b31fee,auto_ml/predictor.py,Predictor,print_results,#Predictor#Any#Any#Any#Any#,836

Before Change

    def print_results(self, model_name, model, X, y):

        feature_responses = None
        if self.advanced_analytics == True:
            feature_responses = self.create_feature_responses(model, X, y)


        if self.ml_for_analytics and model_name in ("LogisticRegression", "RidgeClassifier", "LinearRegression", "Ridge"):
            self._print_ml_analytics_results_linear_model(model, feature_responses)

        elif self.ml_for_analytics and model_name in ["RandomForestClassifier", "RandomForestRegressor", "XGBClassifier", "XGBRegressor", "GradientBoostingRegressor", "GradientBoostingClassifier", "LGBMRegressor", "LGBMClassifier"]:

After Change

        if self.ml_for_analytics and model_name in ("LogisticRegression", "RidgeClassifier", "LinearRegression", "Ridge"):
            df_model_results = self._print_ml_analytics_results_linear_model(model)
            // TODO: only grab the top 100 features from X
            sorted_model_results = df_model_results.sort_values(by="Coefficients", ascending=False)
            sorted_model_results = sorted_model_results.reset_index(drop=True)
            top_features = set(sorted_model_results.head(n=100)["Feature Name"])

            feature_responses = self.create_feature_responses(model, X, y, top_features)
            self._join_and_print_analytics_results(feature_responses, sorted_model_results, sort_field="Coefficients")

Instances