通过逻辑回归方法预测AND,OR运算的输出

Question

我需要设置一个函数来预测 AND、OR 运算的输出。基于输入数组 np.array([[0, 0], [0, 1], [1, 0], [1, 1]]) 并且输出将遵循它们的真值。

 [OR]

[0 0] 0
[0 1] 1
[1 0] 1
[1 1] 1

 [AND]

[0 0] 0
[0 1] 0
[1 0] 0
[1 1] 1

我有代码但是预测功能不正确

import numpy as np
from sklearn.linear_model import LogisticRegression

# Initialize logistic regression model
model = LogisticRegression(solver='lbfgs')

# Train the model with OR input data
X_train = np.array([[0, 0], [0, 1], [1, 0], [1, 1]])
y_train = np.array([0, 1, 1, 1])
model.fit(X_train, y_train)

# Check the output prediction with different input values
X_test = np.array([[0, 0], [0, 1], [1, 0], [1, 1]])
y_pred = model.predict(X_test)

# Print the results
for i in range(len(X_test)):
    print(X_test[i], y_pred[i])