def main(): data_utils = DataUtils() clf_utils = ClassifierUtils() decision_documents, decision_labels = data_utils.load_decision_data() disagreement_documents, disagreement_labels = data_utils.load_disagreement_data( ) clf_metadata = { 'type': 'RF', 'n_estimators': 500, 'max_depth': 128, 'n_jobs': 8 } features_metadata = { 'type': 'count', 'use_sw': True, 'use_length': False, 'binary': False, 'normalize': False, 'append_binary': False, 'sampling': None } metrics = clf_utils.cross_validate(disagreement_documents, disagreement_labels, clf_metadata, features_metadata, num_splits=5) embed()