Improving numerical prediction with qualitative constraints

Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science)

Volumn 2837, Issue , 2003, Pages 385-396

  Šuc, Dorian ^a   Bratko, Ivan ^a  

^a UNIVERSITY OF LJUBLJANA   (Slovenia)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; EXPERT SYSTEMS; FUNCTIONS; LEARNING SYSTEMS; MATHEMATICAL MODELS; MATHEMATICAL TRANSFORMATIONS; PROBLEM SOLVING; QUADRATIC PROGRAMMING; REGRESSION ANALYSIS; TREES (MATHEMATICS); ARTIFICIAL INTELLIGENCE; FORECASTING; POPULATION STATISTICS;

DOMAIN KNOWLEDGE; LINEAR FUNCTIONS; LOGICALLY WEIGHTED REGRESSION (LWR); QFILTER ALGORITHM; BACK-GROUND KNOWLEDGE; LEARNING METHODS; NUMERICAL ACCURACY; NUMERICAL PREDICTIONS; PREDICTION ACCURACY; QUALITATIVE CONSTRAINTS; QUALITATIVE MODEL; REGRESSION METHOD;

CONSTRAINT THEORY; NUMERICAL METHODS;

EID: 9444242738     PISSN: 03029743     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1007/978-3-540-39857-8_35     Document Type: Conference Paper

References (13)

1. Šuc, D., Vladušič, D., Bratko, I.: Qualitatively faithful quantitative prediction. In: Proceedings of the 18th International Joint Conference on Artificial Intelligence. (2003) August, 2003, Acapulco, Mexico.
2. Quinlan, J.: Learning with continuous classes. In: Proc. of the 5th Australian Joint Conference on Artificial Intelligence, Singapore, World Scientific (1992) 343-348
3. Atkeson, C., Moore, A., Schaal, S.: Locally weighted learning. Artificial Intelligence Review 11 (1997) 11-73
4. Witten, I., Frank, E.: Data Mining: Practical Machine Learning Tools and Techniques with Java Implementations, Chapter 8. Morgan Kaufmann, San Francisco (2000) 265-320
5. Šuc, D.: Machine Reconstruction of Human Control Strategies. PhD thesis, Faculty of Computer and Information Sc., University of Ljubljana, Slovenia (2001)
6. Šuc, D., Bratko, I.: Induction of qualitative trees. In De Raedt, L., Flach, P., eds.: Proc. of the 12th European Conf. on Machine Learning, Springer (2001) 442-453
7. Šuc, D., Bratko, I.: Qualitative reverse engineering. In Sammut, C., Hoffmann, A., eds.: Proc. of the 19th International Conf. on Machine Learning, Morgan Kaufmann (2002) 610-617
8. Forbus, K.: Qualitative process theory. Artificial Intelligence 24 (1984) 85-168
9. Kuipers, B.: Qualitative simulation. Artificial Intelligence 29 (1986) 289-338
10. The MathWorks, I.: Matlab software. (2003) http://www.mathworks.com.
11. Coleman, T.F., Li, Y.: A reflective Newton method for minimizing a quadratic function subject to bounds on some of the variables. SIAM Journal on Optimization 6 (1996) 1040-1058
12. Gill, P.E., Murray, W., Wright, M.H.: Quadratic programming. In: Practical Optimization. Academic Press, London, England (1981) 177-184
13. Todorovski, L., Džeroski, S.: Using domain knowledge on population dynamics modeling for equation discovery. In: Proceedings of the 12th European Conference on Machine Learning, Springer (2001) 478-490