第06章 逻辑斯谛回归 - 习题6.2 - 代码实现

import numpy as np
from sklearn.datasets import load_iris
from sklearn.linear_model import LogisticRegression

iris = load_iris()
X = iris.data[:100, :2]
y = iris.target[:100]

lr_clf = LogisticRegression()
lr_clf.fit(X, y)
print("系数:", lr_clf.coef_)
print("截距:", lr_clf.intercept_)