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from matplotlib.colors import ListedColormap
import matplotlib.pyplot as plt
import numpy as np
def plot_decision_regions(X, y, classifier=None, test_idx=None, resolution=0.02):
markers = ("s", "x", "o", "^", "v")
colors = ("red", "blue", "lightgreen", "gray", "cyan")
cmap = ListedColormap(colors[:len(np.unique(y))])
x1_min, x1_max = X[:, 0].min() - 1, X[:, 0].max() + 1
x2_min, x2_max = X[:, 1].min() - 1, X[:, 1].max() + 1
xx1, xx2 = np.meshgrid(np.arange(x1_min, x1_max, resolution), np.arange(x2_min, x2_max, resolution))
Z = classifier.predict(np.array([xx1.ravel(), xx2.ravel()]).T).reshape(xx1.shape)
plt.contourf(xx1, xx2, Z, alpha=0.4, cmap=cmap)
plt.xlim(xx1.min(), xx1.max())
plt.ylim(xx2.min(), xx2.max())
for idx, cl in enumerate(np.unique(y)):
plt.scatter(x=X[y == cl, 0], y=X[y == cl, 1], alpha=0.8, c=cmap(idx), marker=markers[idx], label=cl)
if test_idx:
X_test, y_test = X[test_idx[0]:test_idx[1], :], y[test_idx[0]:test_idx[1]]
plt.scatter(X_test[:,0], X_test[:,1], c = "", alpha=1.0, linewidths=1, marker='o', s=55, label="test set")
if __name__=="__main__":
plot_decision_regions()
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