Support Vector Machine, Support Vector Classifier, Kernel Trick, Rbf, Polynomial.
support vectors ax.scatter(model.support_vectors_[:, 0], model.support_vectors_[:, 1], s=100, linewidth=1, facecolors='none', edgecolors='k') plt.show() C = 1.0 #....defining the model with selected parameters lin_svc = SVC(kernel='linear', C=C).fit(X, y) rbf_svc = SVC(kernel='rbf', gamma=0.7,