# question 12
E_in_list = []
#label, data = utils.load_data('features.train')
print numpy.unique(label)
for C in C_list_log:
clf = SVM.poly_kernel(label, data, 8.0, 2, 1, 1, 10**C)
E_in_list.append(SVM.error_0_1(utils.which_binary(label, 8.0), data, clf))
utils.curve(C_list_log, E_in_list, '12.png', 'log(C)', 'E_in')
# question 13
SV_num_list = []
#label, data = utils.load_data('features.train')
for C in C_list_log:
clf = SVM.poly_kernel(label, data, 8.0, 2, 1, 1, 10**C)
SV_num_list.append(SVM.SV_num(clf))
print SV_num_list
utils.curve(C_list_log, SV_num_list, '13.png', 'log(C)', '#SV')
# question 14
C_list_log = [-3, -2, -1, 0, 1,]
dis_list = []
for C in C_list_log:
clf = SVM.gaussian_kernel(label, data, 0.0, 80, 10**C)
free_SV, free_SV_coef = SVM.free_SV(clf, 10**C)
SV = SVM.get_SV(clf)
SV_coef = SVM.get_dual_coef(clf)
dis = SVM.cal_dis(SV, SV_coef[0], free_SV[0])
dis_list.append(dis)
utils.curve(C_list_log, dis_list, '14.png', 'log(C)', 'dis')
