def test_alpha(number_of_users): res = [] nums = [i for i in range(81) if i > 5 and i % 2 == 0] members, sm_cf, sm_cb, member_to_num, m = pickle_files_for_cv_test() users = get_users(members, number_of_users, nums) auc_res = {} alpha = [i / 60 for i in range(61)] for a in alpha: auc_res[a] = 0 start = mktime(localtime()) for u in users: res_cv = cv(u, 2, sm_cf, sm_cb, member_to_num, m) for tr, res_cf, res_cb in res_cv: for a in alpha: pre, rec, _ = precision_recall_curve(tr, (res_cf * a + (1 - a) * res_cb)) auc_value = auc(rec, pre) auc_res[a] += auc_value for a in alpha: auc_res[a] /= (2 * users.__len__()) print(mktime(localtime()) - start) y = np.zeros(alpha.__len__()) for i, a in enumerate(alpha): y[i] = auc_res[a] print('Ready!') return alpha, y
def all_test(): res = test_alpha(1500) dump('pickle_files/test_alpha.p', res) gc.collect() members, sm_cf, sm_cb, member_to_num, m = pickle_files_for_cv_test() start = mktime(localtime()) res_pre_rec = test(1500, members, sm_cf, sm_cb, member_to_num, m, 0.8, 'pre') print(mktime(localtime()) - start) gc.collect() dump('pickle_files/test_pre_rec.p', res_pre_rec) del res_pre_rec start = mktime(localtime()) gc.collect() res_roc = test(1500, members, sm_cf, sm_cb, member_to_num, m, 0.8, 'ROC') print(mktime(localtime()) - start) dump('pickle_files/test_roc.p', res_roc) return res_pre_rec