Diversified Ensemble Classifiers for Highly Imbalanced Data Learning and their Application in Bioinformatics
In this dissertation, the problem of learning from highly imbalanced data is studied. Imbalance data learning is of great importance and challenge in many real applications. Dealing with a minority class normally needs new concepts, observations and solutions in order to fully understand the underly...
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| Format: | Others |
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Digital Archive @ GSU
2011
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| Online Access: | http://digitalarchive.gsu.edu/cs_diss/60 http://digitalarchive.gsu.edu/cgi/viewcontent.cgi?article=1060&context=cs_diss |