def train_svm_model(feature_frame_train, target_col_name, train_data, y_train,
plots_path, models_path):
train_data_copy = train_data.copy()
model_file_path = str(models_path + 'model_svm.sav')
build_svm_model(train_data_copy, target_col_name, model_file_path)
# Make predictions on the train data and check the model metrics
y_pred_train, y_pred_prob_train = predict(model_file_path,
feature_frame_train)
# Compute confusion matrix on train data
calc_perf_metrics_for_model('svm', y_train, y_pred_train, target_col_name,
plots_path, 'train')
do_roc_analysis(y_train, y_pred_prob_train, 'svm', plots_path, 'train')
def train_gbm_model(feature_frame_train, target_col_name, train_data, y_train,
plots_path, models_path):
train_data_copy = train_data.copy()
model_file_path = str(models_path + 'model_gbm.sav')
build_gbm_model(train_data_copy, target_col_name, model_file_path)
# Make predictions on the train data and check the model metrics
y_pred_train, y_pred_prob_train = predict(model_file_path,
feature_frame_train)
logging.info("describe y_pred_train :: " + str(unique(y_pred_train)))
# Compute confusion matrix on train data
calc_perf_metrics_for_model('gbm', y_train, y_pred_train, target_col_name,
plots_path, 'train')
do_roc_analysis(y_train, y_pred_prob_train, 'gbm', plots_path, 'train')