如何解决R中glmnet中的错误？我希望进行LASSO回归

如何解决如何解决R中glmnet中的错误？我希望进行LASSO回归

我一直收到以下错误：

**Error in elnet(x,is.sparse,ix,jx,y,weights,offset,type.gaussian,: 
                     NA/NaN/Inf in foreign function call (arg 5)**

我知道其他人对此提出了疑问，但是，某些建议的解决方案（例如将X定义为data.matrix）没有用。请在下面找到我的代码：

     CODE: 
                     
                     set.seed(444) 
                 d1 <- read.csv(file = "THP_clean.csv")  ## data file 
                 #some cleaning 
                 d1a <- subset(d1,three_groups !=1)
                 d1b<- DropNA(d1a,Var = "outcome",message = FALSE)
                 df <- data.frame(d1b)
                 
                 library(caret)
                 #split data into training and testing subsamples
                 inTrain <- createDataPartition(y=df$outcome,p=0.7,list=FALSE)
                 training <- df[inTrain,]
                 testing <- df[-inTrain,]
                 
                 # I omitted the actual list of variables here,but this is what the code looks like and there are 20 + explanatory variables. 
                 x<- data.matrix(training[,c("expl_var1","expl_var2","expl_var3" )])
                 
                 # Outcome variable
                 y <- data.matrix(training$outcome)
                 
                 library(glmnet)
                 library(Matrix)
                 
                 fit<- glmnet(Xtrain,Ytrain,family = "gaussian",alpha = 1 )
                 
                 

我要做的就是运行LASSO回归，并找出算法保留的解释变量和丢弃的解释变量。 但是跑步后总是给我错误。从数据集中删除NA（数量不多）并没有帮助。

任何帮助将不胜感激。