Automated discovery of polynomials by inductive genetic programming

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

Volumn 1704, Issue , 1999, Pages 456-461

  Nikolaev, Nikolay ^a   Iba, Hitoshi ^b  

^a AMERICAN UNIVERSITY IN BULGARIA   (Bulgaria)

^b UNIVERSITY OF TOKYO   (Japan)

Author keywords

[No Author keywords available]

Indexed keywords

GENETIC ALGORITHMS; GENETIC PROGRAMMING; POLYNOMIALS;

AUTOMATED DISCOVERY; DATA MINING TASKS; EVOLUTIONARY SEARCH; FITNESS FUNCTIONS; MULTIVARIATE POLYNOMIAL; OPTIMAL SEARCH; STATISTICAL BIAS; VARIANCE COMPONENTS;

DATA MINING;

EID: 84956857723     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-48247-5_58     Document Type: Conference Paper

References (11)

1. Barron, A.R., and Xiao, X. (1991) Discussion on MARS. Annals of Statistics, 19: 67-82.
2. Freitas, A. A. (1997) A Genetic Programming Framework for two Data Mining Tasks: Classification and Generalized Rule Regression. In Genetic Programming 1997: Proc. of the Second Annual Conference, 96-101, Morgan Kaufmann, CA.
3. Gama, J. (1997) Oblique Linear Tree, In X. Liu, P. Cohen, and M. Berthold (Eds.), Advances in Intelligent Data Analysis IDA-97, 187-198, Springer, Berlin.
4. Geman, S., Bienenstock, E., Doursat, R. (1992) Neural Networks and the Bias/Variance Dilemma. Neural Computation, 4(1): 1-58.
5. Iba, H., and de Garis, H. (1996) Extending Genetic Programming with Recombinative Guidance. In Advances in Genetic Programming 2, The MIT Press, 69-88.
6. Ivakhnenko, A. G. (1971) Polynomial Theory of Complex Systems. IEEE Trans. on Systems, Man, and Cybernetics. 1(4): 364-378.
7. Koza, J. R. (1992) Genetic Programming: On the Programming of Computers by Means of Natural Selection. The MIT Press, Cambridge.
8. Merz, C. J., and Murphy, P. M. (1998) UCI Repository of machine learning databases, Irvine, CA: University of California, Dept. of Inf. and Computer Science [www.ics.uci.edu/mlearn/MLRepository.html].
9. Nikolaev, N., and Slavov, V. (1998) Concepts of Inductive Genetic Programming. In EuroGP'98: First European Workshop on Genetic Programming, LNCS-1391, 49-59, Springer, Berlin.
10. Quinlan, R. (1993) C4.5: Programs for Machine Learning. San Mateo, CA: Morgan Kaufmann.
11. Zhang, B.-T., and Mühlenbein, H. (1995). Balancing Accuracy and Parsimony in Genetic Programming. Evolutionary Computation 3(1):17-38.