机器学习(周志华)课后题 第三章 线性模型 3.3

3.3：编程实现对率回归(Logistic Regression)

西瓜数据集3.0α

data = np.array([[0.697, 0.460, 1],
        [0.774, 0.376, 1],
        [0.634, 0.264, 1],
        [0.608, 0.318, 1],
        [0.556, 0.215, 1],
        [0.403, 0.237, 1],
        [0.481, 0.149, 1],
        [0.437, 0.211, 1],
        [0.666, 0.091, 0],
        [0.243, 0.267, 0],
        [0.245, 0.057, 0],
        [0.343, 0.099, 0],
        [0.639, 0.161, 0],
        [0.657, 0.198, 0],
        [0.360, 0.370, 0],
        [0.593, 0.042, 0],
        [0.719, 0.103, 0]])
X_train,X_test,Y_train,Y_test=train_test_split(X_train,Y_train,test_size=0.25,random_state=33)

自定义Logistic函数

def sigmoid(z):
    s = 1 / (1 + np.exp(-z))
    return s