[1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1]] X=np.array(X).transpose() print X.shape y=np.array(y).flatten(1) y[y==0]=-1 print y.shape svms=SVM(X,y) svms.train() print len(svms.supportVector) for i in range(len(svms.supportVector)): t=svms.supportVector[i] print svms.x[:,t] svms.prints_test_linear()
