[R] nnet: cannot coerce class c("terms", "formula") into a data.frame

[cobbler_squad]

Dearest all,

Objective: I am now learning neural networks. I want to see how well can
train an artificial neural network model to discriminate between the two
files I am attaching with this message.

http://r.789695.n4.nabble.com/file/n2240582/3dMaskDump.txt 3dMaskDump.txt 
http://r.789695.n4.nabble.com/file/n2240582/test_vowels.txt test_vowels.txt 

Question: when I am attempting to run 
>cvc_nnet <- nnet(G ~ ., data=cvc_lda, size=1,iter=10,MaxNWts=100)
I get an error saying:
Error in as.data.frame.default(x[[i]], optional = TRUE) : 
  cannot coerce class c("terms", "formula") into a data.frame

I have not encountered this error when I was running this script with
previous lda results, and, I am not quite sure what the error means.

Below is short (and, I hope, reproducible) code. 

library(nnet)

cvc_nnet <- nnet(G ~ ., data=cvc_lda, size=1,iter=10,MaxNWts=100)

predict(cvc_nnet,cvc_lda,type = "class")
table(predict(cvc_nnet,cvc_lda,type = "class"),cvc_lda$G)

cvc_nnet.out<-NULL
all = c(1:52)

for(n in all){
  cvc_nnet <- nnet(G ~ ., data=cvc_lda[all != n,], CV
=TRUE,size=1,iter=10,MaxNWts=100)
   cvc_nnet.out <- c(cvc_nnet.out,predict(cvc_nnet,cvc_lda[all == n,],type =
"class"))
}

table(cvc_nnet.out,cvc_lda$G)

===

to get cvc_lda:

library(MASS)

vowel_features <- data.frame(as.matrix(read.table(file =
"test_vowels.txt")))
mask_features <- data.frame(as.matrix(read.table(file = "3dmaskdump.txt")))
G <-vowel_features[,41]

cvc_lda <- lda(G ~ ., data=mask_features, na.action="na.omit", CV=TRUE)


Your insight is very much appreciated it!

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