【发布时间】：2016-05-16 19:26:10
【问题描述】：
这是对https://stats.stackexchange.com/questions/72251/an-example-lasso-regression-using-glmnet-for-binary-outcome 的引用，我正在尝试将 GLMNET 中的交叉验证（即cv.glmnet）用于二项式目标变量。 glmnet 工作正常，但 cv.glmnet 抛出错误这里是错误日志：
Error in storage.mode(y) = "double" : invalid to change the storage mode of a factor
In addition: Warning messages:
1: In Ops.factor(x, w) : ‘*’ not meaningful for factors
2: In Ops.factor(y, ybar) : ‘-’ not meaningful for factors
数据类型：
'data.frame': 490 obs. of 13 variables:
$ loan_id : Factor w/ 614 levels "LP001002","LP001003",..: 190 381 259 310 432 156 179 24 429 408 ...
$ gender : Factor w/ 2 levels "Female","Male": 2 2 2 2 2 2 2 2 2 1 ...
$ married : Factor w/ 2 levels "No","Yes": 2 2 2 2 1 2 2 2 2 1 ...
$ dependents : Factor w/ 4 levels "0","1","2","3+": 1 1 1 3 1 4 2 3 1 1 ...
$ education : Factor w/ 2 levels "Graduate","Not Graduate": 1 1 1 2 1 1 1 2 1 2 ...
$ self_employed : Factor w/ 2 levels "No","Yes": 1 1 1 1 1 1 1 1 1 1 ...
$ applicantincome : int 9328 3333 14683 7667 6500 39999 3750 3365 2920 2213 ...
$ coapplicantincome: num 0 2500 2100 0 0 ...
$ loanamount : int 188 128 304 185 105 600 116 112 87 66 ...
$ loan_amount_term : Factor w/ 10 levels "12","36","60",..: 6 9 9 9 9 6 9 9 9 9 ...
$ credit_history : Factor w/ 2 levels "0","1": 2 2 2 2 2 2 2 2 2 2 ...
$ property_area : Factor w/ 3 levels "Rural","Semiurban",..: 1 2 1 1 1 2 2 1 1 1 ...
$ loan_status : Factor w/ 2 levels "0","1": 2 2 1 2 1 2 2 1 2 2 ...
使用的代码：
xfactors<-model.matrix(loan_status ~ gender+married+dependents+education+self_employed+loan_amount_term+credit_history+property_area,data=data_train)[,-1]
x<-as.matrix(data.frame(applicantincome,coapplicantincome,loanamount,xfactors))
glmmod<-glmnet(x,y=as.factor(loan_status),alpha=1,family='binomial')
plot(glmmod,xvar="lambda")
grid()
cv.glmmod <- cv.glmnet(x,y=loan_status,alpha=1) #This Is Where It Throws The Error
【问题讨论】：
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怀疑您还需要将
family添加到cv.glmnet。一个例子，`x <- model.matrix(am ~ 0 + . , data=mtcars) ; cv.glmnet(x, y=factor(mtcars$am), alpha=1) ; cv.glmnet(x, y=factor(mtcars$am), alpha=1, family="binomial") -
感谢 user20650 喜欢的魅力
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@user20650 在这种情况下“am”做了什么？
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@AdamRalphus ;这只是一些示例数据：
am是来自mtcars$am的二进制变量，除此之外它与glmnet无关 -
感谢您回答我的问题。我是 glmnet() 的新手。如果我还有其他问题，有什么方法可以联系我吗？