auc acc p r f1score代码怎么写
时间: 2024-05-10 10:16:40 浏览: 11
下面是一个示例代码,计算二分类模型的 AUC、ACC、precision、recall 和 F1-score:
```python
import numpy as np
from sklearn.metrics import roc_auc_score, accuracy_score, precision_score, recall_score, f1_score
# 随机生成样本标签和预测结果
y_true = np.random.randint(0, 2, size=100)
y_pred = np.random.rand(100)
# 计算 AUC
auc = roc_auc_score(y_true, y_pred)
# 计算 ACC
y_pred_binary = np.where(y_pred > 0.5, 1, 0)
acc = accuracy_score(y_true, y_pred_binary)
# 计算 precision、recall 和 F1-score
precision = precision_score(y_true, y_pred_binary)
recall = recall_score(y_true, y_pred_binary)
f1score = f1_score(y_true, y_pred_binary)
print("AUC: %.4f, ACC: %.4f, precision: %.4f, recall: %.4f, F1-score: %.4f" % (auc, acc, precision, recall, f1score))
```
需要注意的是,这里使用了 scikit-learn 库中的相关函数。如果你没有安装该库,可以通过以下命令安装:
```
pip install scikit-learn
```