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Discriminative feature analysis and selection for document classification

Chinta, Punya Murthy and Murty, Narasimha M (2012) Discriminative feature analysis and selection for document classification. In: 19th International Conference, ICONIP 2012, November 12-15, 2012, Doha, Qatar.

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Official URL: http://dx.doi.org/10.1007/978-3-642-34475-6_44

Abstract

Classification of a large document collection involves dealing with a huge feature space where each distinct word is a feature. In such an environment, classification is a costly task both in terms of running time and computing resources. Further it will not guarantee optimal results because it is likely to overfit by considering every feature for classification. In such a context, feature selection is inevitable. This work analyses the feature selection methods, explores the relations among them and attempts to find a minimal subset of features which are discriminative for document classification.

Item Type: Conference Proceedings
Additional Information: Copyright of this article belongs to Springer Berlin Heidelberg.
Keywords: Large Document Collection; Feature Selection Methods; Discriminative Features; Classification; Scalability
Department/Centre: Division of Electrical Sciences > Computer Science & Automation (Formerly, School of Automation)
Date Deposited: 28 May 2013 05:47
Last Modified: 28 May 2013 05:47
URI: http://eprints.iisc.ernet.in/id/eprint/46557

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