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Presentation
Analysing Feature Significance from Various Systems for Mass Diagnosis
International Conference on Computational Intelligence for Modelling, Control and Automation - CIMCA06 Jointly with International Conference on Intelligent Agents, Web Technologies and Internet Commerce - IAWTIC06 (2006)
  • Ping Zhang, University of Queensland
  • Kuldeep Kumar, Bond University
Abstract

This paper compares a few classification models for mass classification and analyzes the feature significance for mass classification using various models. It involves a few algorithms for feature selection and also analyzes the individual feature significance. The comparison of classification models is based on the same datasets for mass diagnosis.

Keywords
  • mass diagnosis,
  • feature significance
Publication Date
November 29, 2006
Comments
Zhang, Ping and Kumar, Kuldeep (2006) Analyzing Feature Significance from Various Systems for Mass Diagnosis is a conference paper presented at the International Conference on Computational Intelligence for Modelling, Control and Automation - CIMCA06 Jointly with International Conference on Intelligent Agents, Web Technologies and Internet Commerce - IAWTIC06 29 November to 1 December 2006 Sydney.
To obtain a copy of this conference paper contact the IEEE Computer Society

2006 HERDC submission
Citation Information
Ping Zhang and Kuldeep Kumar. "Analysing Feature Significance from Various Systems for Mass Diagnosis" International Conference on Computational Intelligence for Modelling, Control and Automation - CIMCA06 Jointly with International Conference on Intelligent Agents, Web Technologies and Internet Commerce - IAWTIC06 (2006)
Available at: http://works.bepress.com/ping_zhang/2/