在Python中使用Sklearn的逻辑回归函数

from sklearn.linear_model import LogisticRegression
from sklearn.model_selection import train_test_split

# 特征变量
X = [[feature1, feature2, ...], [feature1, feature2, ...], ...]

# 目标变量
y = [target1, target2, ...]

X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=0)

logreg = LogisticRegression()
logreg.fit(X_train, y_train)

y_pred = logreg.predict(X_test)

from sklearn.metrics import accuracy_score
accuracy = accuracy_score(y_test, y_pred)