GARF: Towards self-optimised random forests

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

Volumn 7664 LNCS, Issue PART 2, 2012, Pages 506-515

  Bader El Den, Mohamed ^a   Gaber, Mohamed ^a  

^a UNIVERSITY OF PORTSMOUTH   (United Kingdom)

Author keywords

Genetic Algorithms; Random Forest

Indexed keywords

CLASS LABELS; ENSEMBLE CLASSIFICATION; ENSEMBLE LEARNING; EXPERIMENTAL STUDIES; LEARNING APPROACH; RANDOM FORESTS; RF PERFORMANCE; SELECTION METHODS;

DATA PROCESSING; GENETIC ALGORITHMS; LEARNING ALGORITHMS;

DECISION TREES;

EID: 84869061905     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-34481-7_62     Document Type: Conference Paper

References (15)

1. Asuncion, D.N.A.: UCI machine learning repository (2007)
2. Abdulsalam, H., Skillicorn, D.B., Martin, P.: Classification using streaming random forests. IEEE Trans. Knowl. Data Eng. 23, 22-36 (2011)
3. Bader-El-Den, M., Poli, R.: Generating SAT Local-Search Heuristics Using a GP Hyper-Heuristic Framework. In: Monmarché, N., Talbi, E.-G., Collet, P., Schoenauer, M., Lutton, E. (eds.) EA 2007. LNCS, vol. 4926, pp. 37-49. Springer, Heidelberg (2008)
4. Breiman, L.: Bagging predictors. Machine Learning 24, 123-140 (1996)
5. Breiman, L.: Random forests. Machine Learning 45, 5-32 (2001)
6. Breiman, L., Friedman, J.H., Olshen, R.A., Stone, C.J.: Classification and Regression Trees. Statistics/Probability Series.Wadsworth Publishing Company, Belmont (1984)
7. Freund, Y., Schapire, R.E.: A Decision-Theoretic Generalization of On-Line Learning and An Application to Boosting. In: Vitányi, P.M.B. (ed.) EuroCOLT 1995. LNCS, vol. 904, pp. 23-37. Springer, Heidelberg (1995)
8. Haupt, R.L., Haupt, S.E.: Practical Genetic Algorithms. Wiley (2004)
9. Holland, J.H.: Adaptation in natural and artificial systems. MIT Press, Cambridge (1992)
10. Martin-Bautista, M., Vila, M.A.: A survey of genetic feature selection in mining issues. In: Proceedings of the Congress on Evolutionary Computation, CEC 1999, vol. 2 (1999)
11. Norenkov, I.: Scheduling and allocation for simulation and synthesis of cad system hardware. In: Proceedings EWITD 1994, East-West International Conference, ICSTI, Moscow, pp. 20-24 (1994)
12. Robnik-Šikonja, M.: Improving Random Forests. In: Boulicaut, J.-F., Esposito, F., Giannotti, F., Pedreschi, D. (eds.) ECML 2004. LNCS (LNAI), vol. 3201, pp. 359-370. Springer, Heidelberg (2004)
13. Robnik-Sikonja, M., Kononenko, I.: Theoretical and empirical analysis of relieff and rrelieff. Mach. Learn. 53, 23-69 (2003)
14. Sylvester, J., Chawla, N.: Evolutionary ensemble creation and thinning. In: International Conference on Neural Networks, pp. 5148-5155. IEEE (2006)
15. Witten, I.H., Frank, E.: Data Mining: Practical Machine Learning Tools and Techniques, 2nd edn. The Morgan Kaufmann Series in Data Management Systems. Morgan Kaufmann Publishers, San Francisco (2005)