Performance Envelopes of Adaptive Ensemble Data Stream Classifiers
This dissertation documents a study of the performance characteristics of algorithms designed to mitigate the effects of concept drift on online machine learning. Several supervised binary classifiers were evaluated on their performance when applied to an input data stream with a non-stationary clas...
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Format: | Others |
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NSUWorks
2017
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Online Access: | http://nsuworks.nova.edu/gscis_etd/1014 http://nsuworks.nova.edu/cgi/viewcontent.cgi?article=2016&context=gscis_etd |