Title :
An Anomaly Detection-Based Classification System
Author :
Hou, Haiyu ; Dozier, Gerry
Author_Institution :
Auburn Univ., Auburn
Abstract :
In this paper, we describe the construction of a classification system based on an anomaly detection system that employs constraint-based detectors, which are generated using a genetic algorithm. The performance of the classification system was evaluated using two benchmark datasets including the Wisconsin breast cancer dataset and the Fisher´s iris dataset.
Keywords :
genetic algorithms; pattern classification; security of data; anomaly detection system; classification system; constraint-based detector; genetic algorithm; Breast cancer; Computational intelligence; Computer science; Detectors; Fault detection; Immune system; Iris; Software engineering; Target recognition; Training data;
Conference_Titel :
Evolutionary Computation, 2006. CEC 2006. IEEE Congress on
Conference_Location :
Vancouver, BC
Print_ISBN :
0-7803-9487-9
DOI :
10.1109/CEC.2006.1688584
