What would be the best approach to classify a large dataset with sparse
features, into multiple categories. I referred to the multiclass page in the
sklearn documentation, but was not sure on which one to use for multiclass
probabilities [top n probabilities would be nice].
I tried using different classifiers but see some issues:
SGDClassifier: get good result but see "Not Implemented" error when I use
predict_proba
LinearSVC: No method to get probabilities
LDA: get an exception "A sparse matrix was passed, but dense data is
required.
Use X.todense() to convert to dense." upon doing which doesnt work well.
Presently I have 64g limitations on memory and 100g disc space.
Any suggestions?
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