plotting decision boundary of linear classifier

plot_linear_svm.py

import numpy as np 
import matplotlib.pyplot as plt
from sklearn import svm

X = np.array([[-1,-2],[2,6],[-1.5,-2.8],[4,4],[-1,-9.6], [9,11]])                                                   

y = [0,1,0,1,0,1] 

clf = svm.SVC(kernel='linear', C = 1.0,tol=1e-12,random_state=5)

clf.fit(X,y)

w = clf.coef_[0] 

a = -w[0] / w[1] 

xx = np.linspace(-10,12) 

yy = a * xx - clf.intercept_[0] / w[1] 

plt.plot(xx, yy, 'b-',label='decision boundary') 

plt.scatter(X[:, 0], X[:, 1], c = y) 

plt.legend() 

plt.grid()

plt.show()