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Bayesian and Decision Tree Approaches for Pattern Recognition Including Feature Measurement Costs

Dattatreya, GR and Sarma, VVS (1981) Bayesian and Decision Tree Approaches for Pattern Recognition Including Feature Measurement Costs. In: IEEE Transactions on Pattern Analysis and Machine Intelligence, 3 (3). pp. 293-298.

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Abstract

The minimum cost classifier when general cost functionsare associated with the tasks of feature measurement and classification is formulated as a decision graph which does not reject class labels at intermediate stages. Noting its complexities, a heuristic procedure to simplify this scheme to a binary decision tree is presented. The optimizationof the binary tree in this context is carried out using ynamicprogramming. This technique is applied to the voiced-unvoiced-silence classification in speech processing.

Item Type: Journal Article
Additional Information: Copyright 1981 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: 01 Jun 2009 09:06
Last Modified: 19 Sep 2010 05:33
URI: http://eprints.iisc.ernet.in/id/eprint/20526

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