I would like to be able to generate a confidence interval from a model that I create with the package caret. This can be done using predict(model, data, interval = "confidence")
when the model is created with lm()
. However, when I try the same command with a model created with caret's train()
function, I get the following error:
Error in extractPrediction(list(object), unkX = newdata, unkOnly = TRUE, :
unused argument (interval = "confidence")
This is true even when I set method = "lm"
in the train
function. Does anyone know how to get a confidence interval from such an object? Preferably using predict
so the format is the same.
Thanks!
Found out how to do this! caret
objects do in fact store the original model, beneath a huge pile of metadata. You can access this model with my_model_name$finalModel
. Thus, to find the confidence interval, you would call predict(my_model_name$finalModel, my_data, interval = "confidence")
.
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