Journal of Beijing University of Posts and Telecommunications

  • EI核心期刊

JOURNAL OF BEIJING UNIVERSITY OF POSTS AND TELECOM ›› 2006, Vol. 29 ›› Issue (4): 77-80.doi: 10.13190/jbupt.200604.77.zhangl

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A Method for the Selection of Training Samples Based on Boundary Samples

ZHANG Li1,2 , GUO Jun1   

  1. 1. School of Information Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China;
    2. School of Information Technology and Management Engineering, University of International Business and Economics, Beijing 100029, China
  • Received:2005-03-29 Revised:1900-01-01 Online:2006-08-30 Published:2006-08-30
  • Contact: ZHANG Li

Abstract:

Taking the example of designing classifier in intrusion detection system, the selection of training samples for classifier is studied. A new method is proposed for sample selection in large data set. First, it will reduce the size of selection problem via clustering, select samples according to the with-in cluster scatter value and coverage area of a sample. And it will retain boundary samples and discard most of the interior ones in each cluster. As reserving typical samples and reducing training samples, the generalization performance and training efficient of the classifier are guaranteed.

Key words: sample selection, scatter, coverage area, boundary samples

CLC Number: