Dear Mohammadjavad,

This kind of questions are best directed to the scikit-learn mailing
list (and I am forwarding it there).
In this case, as the preimage is just the inverse transformation
between spaces, I don't think it would make much sense to use a
different kernel, so I guess it will be the same one. But I'm not the
best person to ask, I've never even used the Kernel PCA.

Cheers,
Vlad

---------- Forwarded message ----------
From: Vlad Niculae <[email protected]>
Date: Mon, Nov 25, 2013 at 10:41 PM
Subject: Fwd: Problem with scikit learn kernel PCA
To: Vlad Niculae <[email protected]>


On Mon, Nov 25, 2013 at 9:47 PM, Mohammadjavad Vakili <[email protected]> wrote:
> Dear Vlad,
>
> I am currently using the function "inverse_transform" in the kernel PCA
> module and I'm not sure what exactly it does. In the documentation it says
> this is an implementation of "Learning to find the pre-image"(Bakir etal
> 2004).
>
> But my problem is that in the paper they do not specify what the kernel
> (\kappa) they use for learning the pre-image. In scikit learn
> implementation, is that kernel the same kernel (K) used for transformation
> from the original data to the feature space?
>
> Thanks a lot,
> -Mohammadjavad

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