We can now see how our model separates the classes.

xx = np.linspace(-2, 2, 40)
yy = np.linspace(-1.5, 1.5, 40)
gx, gy = np.meshgrid(xx, yy)
Z = model.predict(np.c_[gx.ravel(), gy.ravel()])
Z = Z.reshape(gx.shape)
plt.contourf(gx, gy, Z, cmap=plt.cm.coolwarm, alpha=0.8)

axes = plt.gca()
axes.set_xlim([-2, 2])
axes.set_ylim([-1.5, 1.5])
plt.grid('off')
plt.axis('off')

plt.scatter(X_test[:,0], X_test[:,1], c=prediction_values[:,0], cmap=cm.coolwarm)
plt.title('Model predictions on our Test set')

Text(0.5, 1.0, 'Model predictions on our Test set')