plot_decision_regions.py

from matplotlib.colors import ListedColormap

import numpy as np
import matplotlib.pyplot as plt

def plot_decision_regions(X, y, classifier, 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)
    Z = Z.reshape(xx1.shape)
    plt.contourf(xx1, xx2, Z, alpha = 0.3, 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=colors[idx], marker=markers[idx], label=cl, edgecolors='black')

    if test_idx :
        X_test, y_test = X[test_idx, :], y[test_idx]
        plt.scatter(X_test[:, 0], X_test[:,1], c='', edgecolors='black', alpha=1.0, linewidths=1, marker='o', s=100, label = 'test set')