Dear scikit-learn persons,
This is Pan Yi from the University of Washington, US. I am currently
working on a course project, exploring the performance of
AdaBoostClassifier when using the same base classifier, such as
DecisionTreeClassifier, Perceptron,
KNeighborsClassifier, or mixing different classifiers in one boosting.
Because my input is sparse matrix (41.8MB, mtx format), AdaBoostClassifier
doesn't work unless I change it to dense. The problem is that it will run
out of memory soon.
I want to know whether AdaBoostClassifier and DecisionTreeClassifier have
been improved to work with sparse matrix input X. If not, I need to
implement my own version of AdaBoost that can takes sparse matrix, could
you give me some advice on what kind of change should I make in the code?
Thanks!
--
Best regards,
Yi Pan, B.A.
Archaeology Graduate Student
Department of Anthropology,
University of Washington, U.S.
Mobile: 1-206-484-6519
Email: sallypan...@gmail.com
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