Ensemble Classifier in Data Mining
Performance Enhancement of Classification using Boosting Approach on Noisy Data
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The generalization ability of an ensemble is usually significantly better than that of a single learner, so ensemble methods are very attractive. Authors: Dr. Kalpesh H Vandra is Director Academic and Head in CE/IT department at C. U. Shah College of Engineering, Wadhwan, Guajrat, India. Well known for his research in the areas of Data Mining and Mobile Computing. He had written more than 10 Books related to Computer & IT related area. He is Section Managing Committee Member of ISTE Gujarat Section, Life member of ISTE, member of IEEE and CSI. Dr. Nilesh K Modi is Professor & Head in Computer ...
The generalization ability of an ensemble is usually significantly better than that of a single learner, so ensemble methods are very attractive. Authors: Dr. Kalpesh H Vandra is Director Academic and Head in CE/IT department at C. U. Shah College of Engineering, Wadhwan, Guajrat, India. Well known for his research in the areas of Data Mining and Mobile Computing. He had written more than 10 Books related to Computer & IT related area. He is Section Managing Committee Member of ISTE Gujarat Section, Life member of ISTE, member of IEEE and CSI. Dr. Nilesh K Modi is Professor & Head in Computer Science Department in Sarva Vidyalaya s Institute of Computer Studied, S V Campus, Kadi, Gujarat, India. Well known for his research in the areas of Data Mining and Network Security. He is Associate Life Member in Computer Society of India (CSI) Mumbai, Senior Associate Member in International Association of Computer Science and Information Technology (IACSIT) Singapore, Senior Member in International Association of Engineers (IAEng) Hong Kong, Senior Member in Computer Security Institute New York.
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