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Naive Bayes (Kernel) - optimizing parameters for PhD
Hi! I've been using NB (Kernel) algorithm for my classification problem and I choose a greedy estimation mode.
I also used operator Optimize Parameters (Grid) in order to find the best combination of bandwidth and number of kernels. So, I put that the range of a bandwidth parameter will be from 0.01 to 0.1, and for kernel parameter from 1 to 20.
I've been wondering if these values are in good range and what exactly "number of kernels" parameter stands for? I've been searching the literature for the past few days in order to find some recommended ranges of this parameter and also to find an explanation of the "number of kernels" parameter, but it didn't result in any success.
I would appreciate your help and insights.