One-class genetic programming

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 5481 LNCS, Issue , 2009, Pages 1-12

  Curry, Robert ^a   Heywood, Malcolm I ^a  

^a DALHOUSIE UNIVERSITY   (Canada)

Author keywords

Active learning; Coevolution; One class classification; Problem decomposition

Indexed keywords

ACTIVE LEARNING; ARTIFICIAL DATA; CLASSIFICATION MODELS; CO-EVOLUTIONARY; COEVOLUTION; FALSE POSITIVE; MISCLASSIFICATION; MULTI-OBJECTIVE FITNESS FUNCTION; NOVELTY DETECTION; ONE-CLASS CLASSIFICATION; PROBLEM DECOMPOSITION; TARGET CLASS;

FUNCTION EVALUATION; GENETIC PROGRAMMING; MEMBERSHIP FUNCTIONS; ROUGH SET THEORY; TARGETS;

EQUIVALENCE CLASSES;

EID: 67650675475     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-01181-8_1     Document Type: Conference Paper

References (14)

1. Scholköpf, B., Platt, J., Shawe-Taylor, J., Smola, A., Williamson, R.: Estimating the support of a high-dimensional distribution. Neural Computation 13, 1443-1471 (2001) (Pubitemid 33595028)
2. Tax, D., Duin, R.: Uniform object generation for optimizing one-class classifiers. Journal of Machine Learning Research 2, 155-173 (2001)
3. Zhang, H., Huang, W., Huang, Z., Zhang, B.: A kernel autoassociator approach to pattern classification. IEEE Transactions on Systems, Man and Cybernetics-Part B 35(3), 593-606 (2005) (Pubitemid 40794871)
4. Manevitz, L., Yousef, M.: One-class document classification via neural networks. Neurocomputing 70(7-9), 1466-1481 (2007) (Pubitemid 46336763)
5. Wu, S., Banzhaf, W.: Combatting financial fraud: A coevolutionary anomaly detection approach. In: Genetic and Evolutionary Computation Conference (GECCO), pp. 1673-1680 (2008)
6. Markou, M., Singh, S.: Novelty detection: A review-part 1: Statistical approaches. Signal Processing 83, 2481-2497 (2003)
7. Markou, M., Singh, S.: Novelty detection: A review-part 2: Neural network based approaches. Signal Processing 83, 2499-2521 (2003)
8. Curry, R., Heywood, M.: One-class learning with multi-objective Genetic Programming. In: Proceedings of the IEEE Systems, Man and Cybernetics Conference, SMC, pp. 1938-1945 (2007)
9. Koza, J.: Genetic programming: On the programming of computers by means of natural selection. Statistics and Computing 4(2), 87-112 (1994)
10. Curry, R., Lichodzijewski, P., Heywood, M.: Scaling genetic programming to large datasets using hierarchical dynamic subset selection. IEEE Transactions on Systems, Man and Cybernetics-Part B 37(4), 1065-1073 (2007)
11. Kumar, R., Rockett, P.: Improved sampling of the pareto-front in multiobjective genetic optimizations by steady-state evolution: A pareto converging genetic algorithm. Evolutionary Computation 10(3), 283-314 (2002)
12. Zitzler, E., Thiele, T.: Multiobjective evolutionary algorithms: A comparitive case study and the strength pareto approach. IEEE Transactions on Evolutionary Computation 3(4), 257-271 (1999) (Pubitemid 30544879)
13. Chiu, S.: 9. In: Fuzzy Information Engineering: A Guided Tour of Applications. John Wiley & Sons, Chichester (1997)
14. Asuncion, A., Newman, D.J.: UCI Repository of Machine Learning Databases. Dept. of Information and Comp. Science. University of California, Irvine (2008), http://www.ics.uci.edu/~mlearn/mlrepository.html