在pytorch 中计算精度、回归率、F1 score等指标的实例

# TP predict 和 label 同时为1
TP += ((pred_choice == 1) & (target.data == 1)).cpu().sum()
# TN predict 和 label 同时为0
TN += ((pred_choice == 0) & (target.data == 0)).cpu().sum()
# FN predict 0 label 1
FN += ((pred_choice == 0) & (target.data == 1)).cpu().sum()
# FP predict 1 label 0
FP += ((pred_choice == 1) & (target.data == 0)).cpu().sum()

p = TP / (TP + FP)
r = TP / (TP + FN)
F1 = 2 * r * p / (r + p)
acc = (TP + TN) / (TP + TN + FP + FN