如何计算用sklearn计算recall和Precision

要使用sklearn计算recall和precision，可以使用以下步骤：

导入所需的库和数据集：

from sklearn.metrics import precision_score, recall_score
from sklearn.datasets import make_classification
from sklearn.model_selection import train_test_split

X, y = make_classification(n_samples=1000, n_features=10, random_state=42)
X_train, X_test, y_train, y_test = train_test_split(X, y, random_state=42)

训练模型并进行预测：

from sklearn.linear_model import LogisticRegression

model = LogisticRegression(random_state=42)
model.fit(X_train, y_train)
y_pred = model.predict(X_test)

计算recall和precision：

precision = precision_score(y_test, y_pred)
recall = recall_score(y_test, y_pred)
print("Precision:", precision)
print("Recall:", recall)

输出结果将会显示Precision和Recall的值。