Add rbf_kernel Function

[icfaust]

The rbf kernel converts data via a radial basis function into a new space. This is easy difficulty, but requires significant benchmarking to find when
the scikit-learn-intelex implementation provides better performance. This project will focus on the public API and including the benchmarking
results for a seamless, high-performance user experience. Combines with the other kernel projects to a medium time commitment.

Scikit-learn definition can be found at:
https://scikit-learn.org/stable/modules/generated/sklearn.metrics.pairwise.rbf_kernel.html

The onedal interface can be found at:
https://github.com/uxlfoundation/scikit-learn-intelex/blob/main/onedal/primitives/kernel_functions.py#L70

[tanannie22]

Hi @icfaust, SLintelex_Team2 is interested to work on this! But we are unclear on what is the expected outcome and would like to know more from you. If there are any references or examples we can follow, that would be really helpful.

[icfaust]

Thanks for writing @tanannie22 ! Sorry about not being clearer. As of now, the rbf, polynomial and linear kernel functions are only available in the onedal folder, but we would like to have them available for users via sklearnex. This means we need to write python interfaces in the sklearnex folder which will use the code written in the onedal folder. An example of where this was done recently is this PR: #1957 Where the interfaces for the IncrementalRidge Algorithm was written in sklearnex.