I am using sgdclassifier for document clasification. where (n_samples, n_features) = (12000, 500000). In my project in some of the cases the category chosen leads to post-processing the document and again trying to predict, in which case it should not predict the same category, but return the next best match. There are similar situations where current selected category may be invalid (in terms of the overall solution not classification), and next best match might be selected depending on the algorithm/use case. So -is there a way to predict next best match directly? -or is there a best way to switch to something like knn (which initially showed less promise in terms of predicting correctly) -A
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