def accuracy(self, yhat, y_test, final_cols, model_type):
print("=====================")
print("Accuracy Results")
print("=====================\n")
print(str(model_type))
columns = ['Open', 'High', 'Low', 'Close']
for i in range(0, 4):
print(columns[i])
print("Mean absolute error =",
round(sm.mean_absolute_error(y_test[:, i], yhat[:, i]), 4))
print(
"Mean squared error =",
round(
sm.mean_squared_error(y_test[:, i],
yhat[:, i],
squared=True), 4))
print(
"Explain variance score =",
round(sm.explained_variance_score(y_test[:, i], yhat[:, i]),
4))
print(
"RMSE =",
round(
sm.mean_squared_error(y_test[:, i],
yhat[:, i],
squared=False), 4))
print("R2 score =", round(sm.r2_score(y_test[:, i], yhat[:, i]),
4))
print("\nOverall Accuracy")
print("Mean absolute error =",
round(sm.mean_absolute_error(y_test, yhat), 4))
print("Mean squared error =",
round(sm.mean_squared_error(y_test, yhat, squared=True), 4))
print("Explain variance score =",
round(sm.explained_variance_score(y_test, yhat), 4))
print("RMSE =",
round(sm.mean_squared_error(y_test, yhat, squared=False), 4))
print("R2 score =", round(sm.r2_score(y_test, yhat), 4))
print("R2 score =", round(sm.r2_score(y_test, yhat), 4))
if model_type == 'MLP':
MLP.MLP_analyse(y_test, yhat, final_cols)
if model_type == 'BASELINE':
MLP.MLP_analyse(y_test, yhat, final_cols)
if model_type == 'KNN':
MLP.MLP_analyse(y_test, yhat, final_cols)
if model_type == 'CNN':
LSTMs.LSTM_analyse(self, y_test, yhat, final_cols)
if model_type == 'LSTM':
LSTMs.LSTM_analyse(self, y_test, yhat, final_cols)
# with open('model_config/' + model_type + '.json', 'r') as params:
# json_param = params.read()
# obj = json.loads(json_param)
self.logger.info(model_type)
for i in range(0, 4):
self.logger.info(columns[i])
self.logger.info(
"Mean absolute error =%s",
round(sm.mean_absolute_error(y_test[:, i], yhat[:, i]), 4))
self.logger.info(
"Mean squared error =%s",
round(
sm.mean_squared_error(y_test[:, i],
yhat[:, i],
squared=True), 4))
self.logger.info(
"Explain variance score =%s",
round(sm.explained_variance_score(y_test[:, i], yhat[:, i]),
4))
self.logger.info(
"RMSE =%s",
round(
sm.mean_squared_error(y_test[:, i],
yhat[:, i],
squared=False), 4))
self.logger.info("R2 score =%s",
round(sm.r2_score(y_test[:, i], yhat[:, i]), 4))
self.logger.info("R2 score =%s", round(sm.r2_score(y_test, yhat), 4))
self.logger.info("End\n")
