Clustering and Sample Selection to Enhance the Performance of the Lamstar Intrusion Detection System

Abstract

In the present work, it is proposed to enhance the learning capabilities and reduce the training time of a competitive learning LAMSTAR neural network using Clustering and Sample Selection algorithm. KDDCUP99 reduced feature data set (Features reduced by PCA algorithm) is used for training and testing the various classifiers. KDDCUP99 dataset has five… (More)

Topics

16 Figures and Tables

Cite this paper

@inproceedings{Venkatachalam2008ClusteringAS, title={Clustering and Sample Selection to Enhance the Performance of the Lamstar Intrusion Detection System}, author={V. Venkatachalam and S. Selvan}, year={2008} }