Qualitative inference in possibilistic option decision trees

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

Volumn 3571 LNAI, Issue , 2005, Pages 944-955

  Jenhani, Ilyes ^a   Elouedi, Zied ^a   Ben Amor, Nahla ^a   Mellouli, Khaled ^a  

^a UNIVERSITÉ DE TUNIS   (Tunisia)

Author keywords

[No Author keywords available]

Indexed keywords

CLASSIFICATION (OF INFORMATION); DECISION THEORY; INFORMATION RETRIEVAL; TREES (MATHEMATICS); UNCERTAIN SYSTEMS;

DECISION NODE; POSSIBILISTIC OPTION DECISION TREES (PODT); POSSIBILITY THEORY; QUALITATIVE INFERENCE;

INFERENCE ENGINES;

EID: 26944432301     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/11518655_79     Document Type: Conference Paper

References (12)

1. Ben Amor, N., Benferhat, S., Elouedi, Z.: Qualitative classification and evaluation in possibilistic decision trees, FUZZ-IEEE'2004.
2. Blumer, A., Ehrenfeucht, A., Haussler, D., Warmuth, M.: Occam's razor, Information Processing Letters, 24, 377-380, 1987.
3. Breiman, L., Friedman, J. H., Olshen, R. A., Stone, C. J.: Classification and regression trees, Monterey, CA: Wadsworth & Brooks, 1984.
4. Buntine, W.: Learning classfication trees, Statistics and Computing, 63-73, 1990.
5. Dubois, D., Prade, H.: Possibility theory: An approach to computerized processing of uncertainty, Plenum Press, New York, 1988.
6. Hllermeier, E.: Possibilistic Induction in decision tree learning, ECML'2002.
7. Kohavi, R., Kunz, C.: Option decision trees with majority votes, ICML'97.
8. Murphy, P. M., Aha, D. W., UCI repository of machine learning databases, 1996.
9. Murphy, P. M., Pazzani, M. J.: Exploring the decision forest: An emperical investigation of Occam's Razor in decision tree induction, JAIR, 257-275, 1994.
10. Quinlan, J. R.: Induction of decision trees, Machine Learning, 1, 81-106, 1986.
11. Quinlan, J. R.: C4.5: Programs for machine learning, Morgan Kaufmann, 1993.
12. Weiss, S. M., Kulikovski, C. A.:Computer systems that learn, Morgan Kaufmann, San Mateo, California, 1991.