svm

 

 

 

 

 

 

 

from sklearn import svm


x = [[2, 0], [1, 1], [2, 3]]
y = [0, 0, 1]
clf = svm.SVC(kernel = 'linear')
clf.fit(x, y)

print clf

# get support vectors
print clf.support_vectors_
# get indices of support vectors
print clf.support_
# get number of support vectors for each class
print clf.n_support_