Closed niwak01 closed 2 years ago
I would like to write code I think should be corrected.
import numpy as np
import matplotlib.pyplot as plt
x_min = X_train[:, 0].min() - 1
x_max = X_train[:, 0].max() + 1
y_min = X_train[:, 1].min() - 1
y_max = X_train[:, 1].max() + 1
xx, yy = np.meshgrid(np.arange(x_min, x_max, 0.1),
np.arange(y_min, y_max, 0.1))
f, axarr = plt.subplots(nrows=1, ncols=2,
sharex='col',
sharey='row',
figsize=(8, 3))
for idx, clf, tt in zip([0, 1],
[tree, bag],
['Decision tree', 'Bagging']):
clf.fit(X_train, y_train)
Z = clf.predict(np.c_[xx.ravel(), yy.ravel()])
Z = Z.reshape(xx.shape)
axarr[idx].contourf(xx, yy, Z, alpha=0.3)
axarr[idx].scatter(X_train[y_train == 0, 0],
X_train[y_train == 0, 1],
c='blue', marker='^')
axarr[idx].scatter(X_train[y_train == 1, 0],
X_train[y_train == 1, 1],
c='green', marker='o')
axarr[idx].set_title(tt)
**_#axarr[0].set_ylabel('Alcohol', fontsize=12)
axarr[0].set_ylabel('OD280/OD315 of diluted wines', fontsize = 12)_**
plt.tight_layout()
plt.text(0, -0.2,
**_#s='OD280/OD315 of diluted wines',
s = 'Alcohol',_**
ha='center',
va='center',
fontsize=12,
transform=axarr[1].transAxes)
#plt.savefig('images/07_08.png', dpi=300, bbox_inches='tight')
plt.show()
Ah yes, good catch, you are right! Just updated it! Thanks!
It seems that the positions of the x-label ('Alcohol') and y-label ('OD280/OD315 of diluted wines') are reversed. https://github.com/rasbt/python-machine-learning-book-3rd-edition/blob/master/ch07/images/07_11.png
I am sorry if I am wrong.