逻辑回归,是一种用回归思想解决二分类问题的算法。它是用线性模型去拟合事件的对数几率,其公式化简后,就是著名的Sigmoid函数。逻辑回归通常被用于处理二分类问题,但逻辑回归也可以做多分类,就是Softmax。
from sklearn.datasets import load_breast_cancer from sklearn.linear_model import LogisticRegression from sklearn.model_selection import cross_val_score cancer = load_breast_cancer() x = cancer.data y = cancer.target # 默认参数,L2惩罚项 LR_ = LogisticRegression() score = cross_val_score(LR_, x, y, cv=10).mean() print(score) #0.943 # 改为L1惩罚项 LR_1 = LogisticRegression(penalty='l1', solver='liblinear') score = cross_val_score(LR_1, x, y, cv=10).mean() print(score) #0.950
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