问题
I am trying to fit an autoencoder model using caret. I run into problems because my output will be more than 1-dimensional (e.g. y in the call to train() will be a matrix in my case). Is there a way to account for output of higher dimension in caret?
回答1:
Right now, it only handles univariate outcomes. I'm not sure why you would be using train for an autoencoder though; those are usually used as a pre-processing step rather than the outcome itself.
来源：https://stackoverflow.com/questions/29717969/r-caret-custom-model-with-n-dimensional-output