If there is only one parameter to optimize, then line search is an easy answer.
If there are more than one parameter, then the EvolutionarySearch that we already have can work or any of the many optimization methods from commons.math would apply. ES is better if the parameter space is complicated. On Sat, Jun 8, 2013 at 10:41 PM, Sean Owen <[email protected]> wrote: > Grid search to me is just trying all combinations of values for different > parameters, and you try them with a cross-validation set. They aren't > alternatives. I don't have any knowledge of clustering-related items. > On Jun 8, 2013 7:42 PM, "Saikat Kanjilal" <[email protected]> wrote: > > > Sebastian/Sean, > > Thanks for your responses, first of I am more familiar with cross > > validation than grid search, regardless I'll go ahead and jira up tasks > > for building tools to support both grid search and training error > checking. > > What about the clustering sub-section of the code, is there any > > cleanup/rearchitecture anticipated there ? > > > > >
