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- # View more python learning tutorial on my Youtube and Youku channel!!!
- # Youtube video tutorial: https://www.youtube.com/channel/UCdyjiB5H8Pu7aDTNVXTTpcg
- # Youku video tutorial: http://i.youku.com/pythontutorial
- """
- Please note, this code is only for python 3+. If you are using python 2+, please modify the code accordingly.
- """
- from __future__ import print_function
- from sklearn.learning_curve import learning_curve
- from sklearn.datasets import load_digits
- from sklearn.svm import SVC
- import matplotlib.pyplot as plt
- import numpy as np
- digits = load_digits()
- X = digits.data
- y = digits.target
- train_sizes, train_loss, test_loss= learning_curve(
- SVC(gamma=0.01), X, y, cv=10, scoring='mean_squared_error',
- train_sizes=[0.1, 0.25, 0.5, 0.75, 1])
- train_loss_mean = -np.mean(train_loss, axis=1)
- test_loss_mean = -np.mean(test_loss, axis=1)
- plt.plot(train_sizes, train_loss_mean, 'o-', color="r",
- label="Training")
- plt.plot(train_sizes, test_loss_mean, 'o-', color="g",
- label="Cross-validation")
- plt.xlabel("Training examples")
- plt.ylabel("Loss")
- plt.legend(loc="best")
- plt.show()
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