This is a statistical question, not actually a question about R, and thus not on
topic. Using too many variables leads to models that tend to have large errors
on new data (not from your fitting sample). [1]
[1] https://en.m.wikipedia.org/wiki/Overfitting
On April 19, 2023 6:50:44 AM PDT, akshay kulkarni <akshay_e4 at
hotmail.com> wrote:>Dear members,
> I am doing some modelling with caret package in R.
I do suppose that the package doesn't consider AIC and BIC for model
selection, right? They penalise the number of prameters, but I am ready to spend
a little more time and a little more money to run the model with more number of
parameters, but with a very less SSE.
>
>I know that AIC and BIC are not meant for non parametric ML models, but just
want to confirm....
>
>Thanking you,
>Yours sincerely,
>AKSHAY M KULKARNI
>
> [[alternative HTML version deleted]]
>
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Sent from my phone. Please excuse my brevity.