print("len(fscore_list)")
print(len(fscore_list))
print("len(trained_feature_names)")
print(len(trained_feature_names))
// for idx, result_list in fscore.view:
After Change
print("Here are the feature_importances from the tree-based model:")
print("The printed list will only contain at most the top 50 features.")
for feature in sorted_feature_infos[-50:]:
print(feature[0] + ": " + str(round(feature[1] / sum_of_all_feature_importances, 4)))
def _print_ml_analytics_results_random_forest(self):
print("\n\nHere are the results from our " + self.trained_pipeline.named_steps["final_model"].model_name)
