ePrints@IIScePrints@IISc Home | About | Browse | Latest Additions | Advanced Search | Contact | Help

A Unified Approach to Encoding and Classification Using Bimodal Projection-Based Features

Deodhare, Dipti and Vidyasagar, M and Narasimha Murty, M (2007) A Unified Approach to Encoding and Classification Using Bimodal Projection-Based Features. In: ICCTA '07. International Conference on Computing: Theory and Applications, 2007., 5-7 March 2007, Kolkata .

[img] PDF
A_Unified_Approach.pdf - Published Version
Restricted to Registered users only

Download (205Kb) | Request a copy
Official URL: http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumb...

Abstract

In general the objective of accurately encoding the input data and the objective of extracting good features to facilitate classification are not consistent with each other. As a result, good encoding methods may not be effective mechanisms for classification. In this paper, an earlier proposed unsupervised feature extraction mechanism for pattern classification has been extended to obtain an invertible map. The method of bimodal projection-based features was inspired by the general class of methods called projection pursuit. The principle of projection pursuit concentrates on projections that discriminate between clusters and not faithful representations. The basic feature map obtained by the method of bimodal projections has been extended to overcome this. The extended feature map is an embedding of the input space in the feature space. As a result, the inverse map exists and hence the representation of the input space in the feature space is exact. This map can be naturally expressed as a feedforward neural network.

Item Type: Conference Paper
Additional Information: Copyright 2007 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: 17 Oct 2011 09:34
Last Modified: 17 Oct 2011 09:34
URI: http://eprints.iisc.ernet.in/id/eprint/41486

Actions (login required)

View Item View Item