在Python中使用Logistic回归分析预测向量的准确度得分

import numpy as np
from sklearn.linear_model import LogisticRegression
from sklearn.model_selection import train_test_split
from sklearn.metrics import accuracy_score

# 假设特征向量存储在X中，标签存储在y中
X = np.array([[...], [...], ...])  # 特征向量
y = np.array([...])  # 标签

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

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

y_pred = model.predict(X_test)

accuracy = accuracy_score(y_test, y_pred)