我正在尝试以0.1增量在0和1之间的alpha中计算弹性网中的lambda和Min MSE的不同值。我想输出一个包含三列alpha，lambda和min MSE的表格，以及绘制alpha vs min MSE的图表，但是我一直收到错误消息。我的代码如下所示；
`library(ISLR)
library(glmnet)
alpha <- seq(0, 1, by = 0.1)
min_lambda <- NA
for(i in seq_along(alpha)) {
x=model.matrix(Apps~.,College)[,-1]
y=College$Apps
grid=10^seq(10,-2,length=100)
elnet.mod=glmnet(x,y,alpha=alpha[i],lambda=grid)
set.seed(1)
train=sample(1:nrow(x), nrow(x)/2)
y.test=y[-train]
set.seed(1)
fit.elnet=cv.glmnet(x[train,],y[train],alpha= alpha[i])
min_lambda[i]=fit.elnet$lambda.min
elnet.pred=predict(elnet.mod,s=min_MSE[i],newx=x[-train,])
min_MSE<-mean((elnet.pred-y.test)^2)
}
table(alpha,min_MSE,min_lambda)
plot(alpha,min_MSE)`
我的错误消息是
Error in intI(j, n = x@Dim[2], dn[[2]], give.dn = FALSE) :
'NA' indices are not (yet?) supported for sparse Matrices
> table(alpha,min_MSE,min_lambda)
Error in table(alpha, min_MSE, min_lambda) :
all arguments must have the same length
> plot(alpha,min_MSE)
Error in xy.coords(x, y, xlabel, ylabel, log) :
'x' and 'y' lengths differ
有人可以帮我解决这个问题吗？谢谢