def predicted_vs_actual_y_input_model(self, model, x_train_split, x_test_split, y_train_split, y_test_split,
title_name):
# Split the training data into an extra set of test
# x_train_split, x_test_split, y_train_split, y_test_split = train_test_split(x_train, y_train)
print(np.shape(x_train_split), np.shape(x_test_split), np.shape(y_train_split), np.shape(y_test_split))
model.fit(x_train_split, y_train_split)
y_predicted = model.predict(x_test_split)
plt.figure(figsize=(10, 5))
plt.scatter(y_test_split, y_predicted, s=20)
rmse_pred_vs_actual = self.rmse(y_predicted, y_test_split)
plt.title(''.join([title_name, ', Predicted vs. Actual.', ' rmse = ', str(rmse_pred_vs_actual)]))
plt.xlabel('Actual y')
plt.ylabel('Predicted y')
plt.plot([min(y_test_split), max(y_test_split)], [min(y_test_split), max(y_test_split)])
plt.tight_layout()
two_sigma_financial_modelling.py 文件源码
python
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