Machine Learning, Support Vector Machine, Support Vector Classifier, Data Scie, Svm.
np.meshgrid(np.arange(start = X_set[:, 0].min() - 1, stop = X_set[:, 0].max() + 1, step = 0.01), np.arange(start = X_set[:, 1].min() - 1, stop = X_set[:, 1].max() + 1, step = 0.01)) plt.contourf(X1, X2, classifier_1.predict(sc.transform(np.array([X1.ravel(), X2.ravel()]).T)).reshape(X1.shape),