I would like to ask this loss _ th, change the size, acc does not change, and different loss values, normal acc and abnormal acc values represent the meaning ?
def Analysis_Accuracy_UserDefineLossTH(self, normal_count_list,abnormal_count_list,loss_th=2.0, user_loss_list=None):
show_log = False
normal_correct_cnt = 0
total_normal_cnt = 0
for i in range(len(normal_count_list)):
total_normal_cnt+=normal_count_list[i]
if user_loss_list[i] < loss_th:
normal_correct_cnt+=normal_count_list[i]
if show_log:
print('normal_correct_cnt: {}'.format(normal_correct_cnt))
print('total_normal_cnt: {}'.format(total_normal_cnt))
if total_normal_cnt == 0:
normal_acc = 0.0
else:
normal_acc = float(normal_correct_cnt/total_normal_cnt)
total_abnormal_cnt = 0
abnormal_correct_cnt = 0
for i in range(len(abnormal_count_list)):
total_abnormal_cnt+=abnormal_count_list[i]
if user_loss_list[i] >= loss_th:
abnormal_correct_cnt+=abnormal_count_list[i]
if show_log:
print('abnormal_correct_cnt : {}'.format(abnormal_correct_cnt))
print('total_abnormal_cnt: {}'.format(total_abnormal_cnt))
if total_abnormal_cnt==0:
abnormal_acc = 0
else:
abnormal_acc = float(abnormal_correct_cnt / total_abnormal_cnt)
return normal_acc,abnormal_acc
I would like to ask this loss _ th, change the size, acc does not change, and different loss values, normal acc and abnormal acc values represent the meaning ?
def Analysis_Accuracy_UserDefineLossTH(self, normal_count_list,abnormal_count_list,loss_th=2.0, user_loss_list=None): show_log = False normal_correct_cnt = 0 total_normal_cnt = 0 for i in range(len(normal_count_list)): total_normal_cnt+=normal_count_list[i] if user_loss_list[i] < loss_th: normal_correct_cnt+=normal_count_list[i] if show_log: print('normal_correct_cnt: {}'.format(normal_correct_cnt)) print('total_normal_cnt: {}'.format(total_normal_cnt)) if total_normal_cnt == 0: normal_acc = 0.0 else: normal_acc = float(normal_correct_cnt/total_normal_cnt)