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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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