Methods for Developing Hierarchical Models
Research project, 1997-99, financed by the
Ministry of Science and Technology of the
Republic of Slovenia under grant 3411-97-22-9076.
Project Results
Theory and methodology
- Zupan, B., Bohanec, M., Bratko, I., Demšar, J.:
Machine learning by function decomposition,
in Proceedings ICML-97 (ed. Fisher, D.H.),
pp. 421-429,
San Francisco: Morgan Kaufman Publishers, 1997.
- Zupan, B., Bohanec, M., Demšar, J., Bratko, I.:
Learning by discovering concept hierarchies,
Artificial Intelligence 109, pp. 211-242, 1999.
- Zupan, B., Bratko, I., Bohanec, M., Dem{ar, J.:
Induction of concept hierarchies from noisy data,
in Proceedings of the Seventh International Conference on Machine
Learning ICML-2000 (ed. Langley, P.),
pp. 1199-1206,
San Francisco: Morgan Kaufmann Publishers, 2000.
Partition selection measures
Handling of noise and uncertainty
- Zupan, B,:
Machine learning based on function decomposition,
Ph.D. Thesis, University of Ljubljana, 1997.
Decomposition of real-valued functions
- Demšar, J., Zupan, B., Bohanec, M., Bratko, I.:
Constructing intermediate concepts by decomposition of real functions,
in Machine Learning: ECML-97 (eds. van Someren, M., Widmer, G),
pp. 93-107,
Berlin: Springer-Verlag, 1997.
Applicability of function decomposition
- For Decision Support:
- Bohanec, M., Zupan, B., Bratko, I., Cestnik, B.:
A function-decomposition method for development of hierarchical
multi-attribute decision models,
in Proceedings of the Fourth Conference of the International
Society for Decision Support Systems ISDSS-97,
pp. 503-514,
Lausanne, 1997.
- For Knowledge Discovery in Databases (KDD):
- Zupan, B., Bohanec, M., Bratko, I., Cestnik B.:
A dataset decomposition approach to data mining and machine discovery,
in Proc. of the Third International Conference on Knowledge
Discovery and Data Mining (KDD-97) (eds. Heckerman, D., Mannila, H.,
Pregibon, D., Uthurusamy, R.),
pp. 299-303. AAAI Press, 1997.
- For Feature Transformation:
- Zupan, B., Bohanec, M., Demšar, J., Bratko I.:
Feature transformation by function decomposition,
IEEE Intelligent Systems 13(2), pp. 38-43, 1998.
(abstract).
- Zupan, B., Bohanec, M., Demšar, J., Bratko I.:
Feature transformation by function decomposition,
in Feature extraction, construction and selection: A data
mining perspective (eds. Liu, H., Motoda, H.),
pp. 325-340, Kluwer Academic Publishers, 1998.
- Applications in Medicine:
- Zupan, B., Halter, J.A., Bohanec, M.:
Concept Discovery by Decision Table Decomposition and its
Application in Neurophysiology,
in Intelligent data analysis in medicine and pharmacology
(eds. Lavrač, N., Keravnou, E., Zupan, B.),
pp. 261-277, Kluwer, 1997.
- Bohanec, M., Zupan, B., Rajkovič, V:
Hierarhični odločitveni modeli in njihova uporaba v zdravstvu,
Zbornik CADAM-97: Računalniška analiza medicinskih podatkov
(eds. I. Kononenko, T. Urbančič),
Institut Jožef Stefan, 1-17, 1997.
- Applications in Socioeconomic Research:
- Krisper, M., Zupan, B.:
Synthesis of hierarchical decision support models from socioeconomic data,
Zbornik konference Informacijska družba
(eds. Bavec, C., Gams. M.), Institut Jožef Stefan, 60-63, 1998.
Methods and tools for hierarchical decision models
- Bohanec, M., Cestnik, B., Rajkovič, V.:
Evaluation models for housing loan allocation in the context of floats,
in Context sensitive decision support systems
(eds. Berkeley, D., Widmeyer, G.R., Brezillon, P., Rajkovič, V.),
Chapman & Hall, pp. 174-189, 1998.
- Grohar, B., Bohanec, M., Rajkovič, V.:
DexW: Računalniški program za delo s kvalitativnimi
večparametrskimi odločitvenimi modeli,
Zbornik sedme Elektrotehniške in računalni{ke konference ERK'98
(ed. Zajc, B.), Portorož, 107-110, 1998.
The machine learning method based on function decomposition was
implemented in the C language as a system called HINT (Hierarchy
INduction Tool). This research prototype system runs on several UNIX
platforms, including HP-UX, SGI Iris, and SunOS. The definition of
domain names and examples, and the guidance of the decomposition is
managed through a script language.
After the termination of this project, HINT has been incorporated into
Orange,
a public domain data mining software developed at the
University of Ljubljana,
Faculty of Computer and Information Science.