Enhanced Algorithm Performance for Classification Based on Hyper Surface using Bagging and Adaboost

To improve the generality ability of Hyper Surface Classification (HSC) , Bagging and AdaBoost ensemble learning methods are proposed in this paper. HSC is a covering learning algorithm, in which a model of hyper surface is obtained by adaptively dividing the sample space and then the hyper surface...

Ausführliche Beschreibung

Bibliographische Detailangaben

Hauptverfasser:	Qing He, Fu-Zhen Zhuang, Xiu-Rong Zhao, Zhong-Zhi Shi
Format:	Tagungsbericht
Sprache:	eng
Schlagworte:	AdaBoost Bagging Boosting Business process re-engineering Classification algorithms Cognition Hyper surface cassification Learning systems Minimal consistent subset Pattern recognition Topology Voting
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