Construction of the Training Data Set in Intrusion Detection Systems Based on the Agglomerate Clustering Algorithm
Feng Li · Computer Engineering and Science · 2009
A constructing method is proposed to train the data set in intrusion detection systems in this paper.First,through retraining the boundary and discarding most of the interior training samples,we select important samples from classes containing more samples,construct virtual samples for the class that contains less samples in the way of combining the genetic algorithm and the agglomerate clustering algorithm.The number of the training subset samples gained in this way is few and its distribution is symmetrical.