Optimizing decision trees using multi-objective particle swarm optimization

Studies in Computational Intelligence

Volumn 242, Issue , 2009, Pages 93-114

  Fieldsend, Jonathan E ^a  

^a UNIVERSITY OF EXETER   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 70349774614     PISSN: 1860949X     EISSN: None     Source Type: Book Series    
DOI: 10.1007/978-3-642-03625-5_5     Document Type: Article

References (26)

1. Bishop, C.: Pattern Recognition and Machine Learning. Information Science and Statistics. Springer, Heidelberg (2006)
2. Duda, R., Hart, P.: Pattern Classification and Scene Analysis, 2nd edn. Wiley, Chichester (2001)
3. Everson, R., Fieldsend, J.: Multi-objective optimization of safety related systems: An application to short term conflict alert. IEEE Transactions on Evolutionary Computation 10, 187-198 (2006)
4. Schetinin, V., Fieldsend, J., Partridge, D., Coats, T., Krzanowski, W., Everson, R., Bailey, T., Hernandez, A.: Confident interpretation of bayesian decision tree ensembles for clinical applications. IEEE Transactions on Information Technology in Biomedicine 11, 312-319 (2007)
5. Asuncion, A., Newman, D.: UCI machine learning repository (2007)
6. Ripley, B.: Neural networks and related methods for classification (with discussion). Journal of the Royal Statistical Society Series B 56, 409-456 (1994)
7. Brieman, L., Friedman, J., Olshen, R., Stone, C.: Classification and Regression Trees. Chapman & Hall/CRC (1984)
8. Quinlan, J.: Induction of decision trees. Machine Learning 1, 86-106 (1986)
9. Quinlan, J.: C4.5 Programs for Machine Learning. Morgan Kaufmann, San Francisco (1993)
10. Kennedy, J., Eberhart, R.: Particle swarm optimization. In: IEEE International Conference on Neural Networks, Perth, Australia, pp. 1942-1948. IEEE Service Center (1995)
11. Kennedy, J., Eberhart, R.: A discrete binary version of the particle swarm algorithm. In: Proceedings of the IEEE Conference on Systems, Man and Cybernetics, pp. 4104-4109. IEEE Press, Los Alamitos (1997)
12. Kim, D.: Minimizing structural risk on decision tree classification. In: Jin, Y. (ed.) Multi-Objective Machine Learning. Studies in Computational Intelligence, vol. 16, pp. 241-260. Springer, Heidelberg (2006)
13. Denison, D., Holmes, C., Mallick, B., Smith, A.: Bayesian Methods for Nonlinear Classification and Regression. Probability and Statistics. Wiley, Chichester (2002)
14. Veenhuis, C., Köppen, M., Krüger, J., Nickolay, B.: Tree swarm optimization: An approach to pso-based tree discovery. In: 2005 IEEE Congress on Evolutionary Computation, vol. 2, pp. 1238-1245 (2005)
15. Everson, R., Fieldsend, J.: Multi-class roc analysis from a multi-objective optimisation perspective. Pattern Recognition Letters 27, 918-927 (2006)
16. Everson, R., Fieldsend, J.: Multi-objective optimisation for receiver operating characteristic analysis. In: Jin, Y. (ed.) Multi-Objective Machine Learning. Studies in Computational Intelligence, vol. 16, pp. 531-556. Springer, Heidelberg (2006)
17. Fieldsend, J.: Multi-objective particle swarm optimisation methods. Tech. Rep. 419, Department of Computer Science, University of Exeter (2004)
18. Coello Coello, C., Pulido, G., Lechuga, M.: Handling multiple objectives with particle swarm optimization. IEEE Transactions on Evolutionary Computation 8, 256-279 (2004)
19. Alvarez-Benitez, J., Everson, R., Fieldsend, J.: A mopso algorithm based exclusively on pareto dominance concepts. In: The Third International Conference on Evolutionary Mutli-Criterion Optimization, pp. 459-473 (2005)
20. Fieldsend, J., Everson, R., Singh, S.: Using unconstrained elite archives for multiobjective optimization. IEEE Transactions on Evolutionary Computation 7, 305-323 (2003)
21. Fieldsend, J., Singh, S.: A multi-objective algorithm based upon particle swarm optimisation, an efficient data structure and turbulence. In: 2002 UK Workshop on Computational Intelligence (UKCI 2002), Birmingham, UK, pp. 37-44 (2002)
22. Fieldsend, J., Singh, S.: Pareto evolutionary neural networks. IEEE Transactions on Neural Networks 16, 338-354 (2005)
23. Knowles, J., Watson, R., Corne, D.: Reducing local optima in single-objective problems by multi-objectivization. In: Zitzler, E., Deb, K., Thiele, L., Coello Coello, C.A., Corne, D.W. (eds.) EMO 2001. LNCS, vol. 1993, pp. 269-283. Springer, Heidelberg (2001)
24. Jensen, M.: Guiding single-objective optimization using multiobjective methods. In: Raidl, G.R., Cagnoni, S., Cardalda, J.J.R., Corne, D.W., Gottlieb, J., Guillot, A., Hart, E., Johnson, C.G., Marchiori, E., Meyer, J.-A., Middendorf, M. (eds.) EvoIASP 2003, EvoWorkshops 2003, EvoSTIM 2003, EvoROB/EvoRobot 2003, EvoCOP 2003, EvoBIO 2003, and EvoMUSART 2003. LNCS, vol. 2611, pp. 268-279. Springer, Heidelberg (2003)
25. Abbass, H., Deb, K.: Searching under multi-evolutionary pressures. In: Fonseca, C.M., Fleming, P.J., Zitzler, E., Deb, K., Thiele, L. (eds.) EMO 2003. LNCS, vol. 2632, pp. 391-404. Springer, Heidelberg (2003)
26. Mostaghim, S., Teich, J.: Strategies for finding good local guides in multi-objective particle swarm optimization (mopso). In: IEEE 2003 Swarm Intelligence Symposium (2003)