On Fri, Aug 2, 2013 at 6:28 AM, yikes aroni <[email protected]> wrote:
> Hmm. Interesting indeed. And the real bonus is that i get it. Sounds like > the solution to the problem of large numbers of target classes is to > develop a sensible scheme for grouping the target classes s.t. you can > reduce the number of them required per training run, then run the training > once on each sub-set of target classes. To query, you simply query this > large number of classifiers to build up your answer. > You may have thousands of classifiers in toto, but you should only have to evaluate dozens of them. > > Is that the common practice? > Having training data for 60,000 categories is quite rare in my experience. > > thank you for your time, Mr. Dunning. > NP. Send feedback if you implement such a beast.
