logistics 预测
时间: 2023-10-27 07:07:16 浏览: 122
回答: Logistic回归是一种用于预测分类问题的统计模型。它基于线性回归,并使用logistic函数将线性回归的结果映射到0和1之间的概率值。[1] Sigmoid函数,也称为logistic函数,是logistic回归中使用的函数,它可以将线性回归的函数值映射到区间(0,1),作为概率输出。当概率大于等于0.5时,我们将其判定为正类,小于0.5时判定为负类。[2]因此,logistic回归可以用于二分类问题,也可以通过多次运行来实现多分类问题。[2]在logistic回归中,因变量y的值在0和1之间,可以看作是属于类别1的概率。当0.5≤y≤1时,我们可以判定为类别1,否则判定为类别0。[3]
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