from matplotlib.colors import ListedColormap
X_set, y_set = X_train, y_train
X1, X2 = 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))

pred = classifier.decision_function(np.array([X1.ravel(), X2.ravel()] + [np.repeat(0, X1.ravel().size) for _ in range(12)]).T).reshape(X1.shape)
plt.contourf(X1, X2, pred,
             alpha=1.0, cmap="RdYlGn", levels=np.linspace(pred.min(), pred.max(), 100))

plt.xlim(X1.min(), X1.max())
plt.ylim(X2.min(), X2.max())
for i, j in enumerate(np.unique(y_set)):
    plt.scatter(X_set[y_set == j, 0], X_set[y_set == j, 1], c = ListedColormap(('red', 'green'))(i), label = j)
plt.title('SVM (Training set)')
plt.xlabel('Age')
plt.ylabel('Lung Cancer')
plt.legend()
plt.show()