Support Vector Machine, Support Vector Classifier, Kernel Trick, Rbf, Polynomial.
def plot_svm_boundary(model,X,y): X = X.values y = y.values # Scatter Plot plt.scatter(X[:, 0], X[:, 1], c=y, s=30,cmap='seismic') # plot the decision function ax = plt.gca() xlim = ax.get_xlim() ylim = ax.get_ylim() # create grid to evaluate model xx = np.linspace(xlim[0], xlim[1], 30) yy =