alphas_full[sv_idx] = alphas
alphas_full = alphas_full * y
print "svmlight objective:", svm.get_objective()
print "svmlight alphas:", numpy.array(alphas_full[0:5])
external_objective = 0.0
for j in xrange(N):
external_objective += alphas_full[j] * f[j]
for k in xrange(N):
external_objective += 0.5 * alphas_full[j] * alphas_full[k] * y[j] * y[k] * wdk.kernel(j,k)
print "svmlight external objective:", external_objective
#precompute kernel matrix using shogun
K = wdk.get_kernel_matrix()
K = numpy.transpose(y.flatten() * (K*y.flatten()).transpose())
C = 1.0
# Important!! QP does not accept ndarray as a type, it must be an array
p = QP(K, f, Aeq=y, beq=0, lb=numpy.zeros(N), ub=C*numpy.ones(N))
r = p.solve('cvxopt_qp', iprint = 0)
