visualise classifier borders

clf_borders.py

X_train = ... # (n,2) numpy array dataset

# Create a meshgrid
x_min, x_max = X_train[:, 0].min() - 1, X_train[:, 0].max() + 1
y_min, y_max = X_train[:, 1].min() - 1, X_train[:, 1].max() + 1
xx, yy = np.meshgrid(np.arange(x_min, x_max, 0.1),
                     np.arange(y_min, y_max, 0.1))
                     
                     
# Make predictions on the meshgrid
preds = clf.predict(np.c_[xx.ravel(), yy.ravel()])
Z = preds.reshape(xx.shape)


# Visualize the boundaries
plt.contourf(xx, yy, Z, cmap=plt.cm.Paired, alpha=0.8)
plt.scatter(X_train.values[:, 0], X_train[:, 1], c=y_train, cmap=plt.cm.Paired)
plt.show()