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问题描述
我很想尝试解决这个问题.我如何在R中定义在二进制逻辑回归中使用的参考水平?多项式逻辑回归又如何呢?现在我的代码是:
I am going nuts trying to figure this out. How can I in R, define the reference level to use in a binary logistic regression? What about the multinomial logistic regression? Right now my code is:
logistic.train.model3 <- glm(class~ x+y+z,
family=binomial(link=logit), data=auth, na.action = na.exclude)
我的响应变量是是"和否".我想预测某人回答是"的可能性.
my response variable is "YES" and "NO". I want to predict the probability of someone responding with "YES".
我不想将变量重新编码为0/1.有什么方法可以告诉模型预测是"?
I DO NOT want to recode the variable to 0 / 1. Is there a way I can tell the model to predict "YES" ?
谢谢您的帮助.
推荐答案
假定您将类保存为一个因子,请使用relevel()
函数:
Assuming you have class saved as a factor, use the relevel()
function:
auth$class <- relevel(auth$class, ref = "YES")
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