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Hybrid Learning Scheme for Data Mining Applications

Babu, Ravindra T and Murty, Narasimha M and Agrawal, VK (2004) Hybrid Learning Scheme for Data Mining Applications. In: Fourth International Conference on Hybrid Intelligent Systems, 2004, 5-8 December, Kitakyushu,Japan, 266 -271.

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Abstract

Classification of large datasets is a challenging task in data mining. In the current work, we propose a novel method that compresses the data and classifies the test data directly in its compressed form. The work forms a hybrid learning approach integrating the activities of data abstraction, frequent item generation, compression, classification and use of rough sets.

Item Type: Conference Paper
Additional Information: ©1990 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Department/Centre: Division of Electrical Sciences > Computer Science & Automation (Formerly, School of Automation)
Date Deposited: 23 Jan 2007
Last Modified: 19 Sep 2010 04:21
URI: http://eprints.iisc.ernet.in/id/eprint/4250

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