吴恩达-机器学习-逻辑回归模型实现

吴恩达-机器学习2022-逻辑回归模型sklearn实现

import numpy as np
from sklearn.linear_model import LogisticRegression

#初始化数据
X = np.array([[0.5, 1.5], [1,1], [1.5, 0.5], [3, 0.5], [2, 2], [1, 2.5]])
y = np.array([0, 0, 0, 1, 1, 1])


#初始化模型
lr_model = LogisticRegression()
lr_model.fit(X, y)

#预测
y_pred = lr_model.predict(X)

print("Prediction on training set:", y_pred)

print("Accuracy on training set:", lr_model.score(X, y))

输出结果

#输出结果
Prediction on training set: [0 0 0 1 1 1]
Accuracy on training set: 1.0