Some heuristics for default knowledge discovery

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

Volumn 1424, Issue , 1998, Pages 373-380

  Jenssen, Tor Kristian ^a   Komorowski, Jan ^a   Øhrn, Aleksander ^a  

^a NORWEGIAN UNIVERSITY OF SCIENCE AND TECHNOLOGY   (Norway)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; COMPUTER SCIENCE; COMPUTERS;

DECISION RULES; S-ALGORITHMS;

ROUGH SET THEORY;

EID: 28244452904     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/3-540-69115-4_51     Document Type: Conference Paper

References (22)

1. Brewka, G. NonmonotonicReasoning: Logical Foundations of Commonsense, Cambridge University Press, 1991
2. Fayyad, U. M., Piatetsky-Shapiro, G., Smyth, P., and Uthurasamy, R. (eds.) Advances in Knowledge Discovery and Data Mining, AAAI Press/MIT Press, 1996
3. Hanley, J. A. and McNeil, B. J. The Meaning and Use of the Area under a Receiver Operating Characteristic (ROC) Curve, Radiology, 143, pp. 29-36, 1982
4. Holte, R. C. Very simple classification rules perform well on most commonly used datasets, Machine Learning, 11, pp. 63-90
5. Jenssen, T.-K. Refinements to Mollestad’s Algorithm for Synthesis of Default Rules, MSc Thesis, Norwegian University of Science and Technology, 1998
6. Lukaszewics, W. Non-Monotonic Reasoning formalization of commonsence reasoning, Ellis Horwood, 1990
7. Mollestad, T. Learning Propositional Default Rules using the Rough Set Approach, In: Aamodt, A. and Komorowski, J. (eds.), Scandinavian Conference on Artificial Intelligence, pp. 208-219, IOS Press, 1995
8. Mollestad, T. and Skowron, A. A Rough Set Framework for Data Mining of Propositional Default Rules, In: Michalewicz, Z. and Ras, Z. R. (eds.), Proc. of the 9th Intl. Symposium on Intelligent Systems, ISMIS ‘96, pp. 448-457, Springer Verlag, 1996
9. Mollestad, T.: A Rough Set Approach to Data Mining: Extracting a logic of default rules from data, PhD Thesis, Norwegian University of Science and Technology, 1997
10. Mollestad, T. and Komorowski, J.: A Rough Set Framework for Propositional Default Rules Data Mining, To appear in: Pal, S. K. and Skowron, A. (eds.), Fuzzy Sets, Rough Sets and Decision Making Processes, Springer-Verlag Singapore Pte Ltd, 1998
11. Murphy, P. M. UCI Repository of machine Learning and Domain Theories, At: http://www.ics.uci.edu/~mlearn/MLRepository.html
12. Pawlak, Z. Rough Sets, In: Intl. J. of Information and Computer Science, 11(5) pp. 341-356, 1982
13. Pawlak, Z. Rough Sets: Theoretical Aspects of Reasoning about Data, Kluwer Academic Publisher, 1991
14. Pawlak, Z. and Skowron A. A Rough Set Approach to Decision Rules Generation, Technical Report, Warzaw University of Technology, 1993
15. Piatetsky-Shapiro, G. and Frawley, W. J. (eds.) Knowledge Discovery in Databases, AAAI Press/MIT Press, 1991
16. Poole, D. L. A Logical Framework for Default Reasoning, J. of Artificial Intelligence, 36, pp. 27-47, 1988
17. Reiter, R. A Logic for Default Reasoning, Computational Intelligence, 13, pp. 81132, 1980
18. The RosettaWWW homepage At: http://www.idi.ntnu.no/~aleks/rosetta/
19. Skowron, A. Boolean Reasoning for Decision Rules Generation In: Komoroski, J. and Ras, Z. W. (eds.), 7th Intl. Symposium for Methodologies for Intelligent Systems (ISMIS ‘93), pp. 295-305, Springer Verlag, 1993
20. Skowron, A. Synthesis of Adaptive Decision Systems from Experimental Data, In: Aamodt, A. and Komorowski, J. (eds.), Proc. 5th Scandinavian Conference on Artificial Intelligence, Trondheim, Norway, May 29-31, Frontiers in Artificial Intelligence and Applications, Vol. 28, pp. 220-238, IOS Press, 1995
21. Ziarko, W. P. (ed.) Rough Sets, Fuzzy Sets, and Knowledge Discovery Proc. of the Intl. Workshop on Rough Sets and Knowledge Discovery (RSKD ‘93), Springer Verlag, 1993
22. Øhrn, A., Komorowski, J., Skowron, A. and Synak, P. The Design and Implementation of a Knowledge Discovery Toolkit Based on Rough Sets The RosettaSystem, To appear in: Skowron, A. and Polkowski, L. (eds.), Rough Sets in Knowledge Discovery, Physica Verlag