I'm using caret to train models over resamples and tune learning parameters, and I can interrogate the probabilities for each test, which is great. But I'm also keen to retain the model objects and use them later without retraining -- is this possible? Basically rather than just the mdl$finalModel object, I'd like the model object for each iteration of tuning.
Not really. You could write a custom method and modify the fit
function to save them out to a file. Inside the fit
function, you would know the tuning parameter value but not what resample that the model was build with.
Max
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