Spliting training data into multiple variables using R

Question

So right now I am trying to create multiple variables with training data, and in the process I have reached an error

Error in eval(predvars, data, env) : object '1.band1' not found

which is a product of these lines:

for(i in 1:length(data_split)){ assign(paste("fit.lda",i, sep = ""), train(class~., data=data_split[i], method="lda", metric=metric, trControl=control))}

is it something that I did wrong or is it something that can be fixed with another methodology

EDIT: My dataset is a data frame which was created by the following lines

validation_index <- createDataPartition(valuetable$class, p=0.80, list=FALSE) dataset <- valuetable[validation_index,]

where valuetable is a dataframe which containes the values of multiple rasters.

Now, I wanted to split my data so my train function can be processed faster, that is because my machine's specs are pretty low, thus allowing me to re-create the later the results that would take time using other methods.

Let me know if you want more clarification.

Answer 1

You didn't explained how is your dataset and its variables, so I'll put a generic example.

Let's say your dataset has a variable called SET, whose content is TRN for training and TST for test. To create a dataset containing only training set you have to use the following code:

trn.ds<- ds[ds$SET == 'TRN',]

If you need a test dataset, just adapt the code:

tst.ds<- ds[ds$SET == 'TST']

PS: It wasn't me who downvoted your question, I don't understand why people downvote almost every question here.