I am clustering some real world text data using K-Means. I recently came across Kernel K-Means and wanted to know if someone who has had experience with Kernels could comment on their appropriateness for text data, i.e, Would using a Kernel boost k-means quality? ( I know this is rather general but it is sort of hard to figure out if my high dimensional real world data is linearly separable.) If so, are there any Kernel's with "practically accepted" parameters?
Thanks VC
