y_pred_MLP55 = Predictor(regressor_MLP55, x_train, y_train,
x_test).predict()
y_pred_MLP2020 = Predictor(regressor_MLP2020, x_train, y_train,
x_test).predict()
results_RF5 = Results(y_test, y_pred_RF5, i, 'RF', 'RF5')
results_RF20 = Results(y_test, y_pred_RF20, i, 'RF', 'RF20')
results_MLP55 = Results(y_test, y_pred_MLP55, i, 'MLP', 'MLP55')
results_MLP2020 = Results(y_test, y_pred_MLP2020, i, 'MLP', 'MLP2020')
results_RF5.save_to_txt()
results_RF20.save_to_txt()
results_MLP55.save_to_txt()
results_MLP2020.save_to_txt()
arrays_RF5.append_array(results_RF5.mse, results_RF5.mae, results_RF5.mape,
results_RF5.r2)
arrays_RF20.append_array(results_RF20.mse, results_RF20.mae,
results_RF20.mape, results_RF20.r2)
arrays_MLP55.append_array(results_MLP55.mse, results_MLP55.mae,
results_MLP55.mape, results_MLP55.r2)
arrays_MLP2020.append_array(results_MLP2020.mse, results_MLP2020.mae,
results_MLP2020.mape, results_MLP2020.r2)
# Create a workbook for each iteration and saves all the tests id different sheets
with pd.ExcelWriter('./results/estimated/RF/RF_OutputSeed_{}.xlsx'.format(
i)) as writer: # pylint: disable=abstract-class-instantiated
pd.DataFrame(y_pred_RF5,
columns=['Predicted']).to_excel(writer,
sheet_name='RF5',
index=False)
pd.DataFrame(y_test, columns=['Measured']).to_excel(writer,
