Child well being estimation as a multi-criteria decision problem

• Autorzy: Adamus E. , Klęsk P. , Kołodziejczyk J. , Korzeń M. , Piegat A. , Pluciński M.
• Języki publikacji: EN

Abstrakty

EN

The aim of the article is to establish a list of capabilities with reference to children’s well being in Poland. This issue can be considered as a multicriterial classification problem where decision attributes classes are ordered due to the preference – criteria. We used a Dominance-based Rough Set Approach (DRSA) adapted to deal with missing values. Analysis was performed on data set collected in Zachodniopomorskie district as a result of survey conduction.

Słowa kluczowe

EN

missing values; child well being measurement; survey; childhood; Poland; multi-criteria decision problem; dominance-based rough set approach; DRSA

PL

brakujące wartości; pomiar dobrobytu dziecka; ankieta dotycząca dzieciństwa w Polsce; problem decyzji multi-kryterialnej; dominacja

• Wydawca: Komisja Informatyki Polskiej Akademii Nauk, Oddział w Gdańsku
• Czasopismo: Metody Informatyki Stosowanej
• Rocznik: 2011
• Tom: nr 4
• Strony: 279--286
• Opis fizyczny: Bibliogr. 10 poz., rys.

Twórcy

autor

Adamus E.

autor

Klęsk P.

autor

Kołodziejczyk J.

autor

Korzeń M.

autor

Piegat A.

autor

Pluciński M.

• West Pomeranian University of Technology, Szczecin Faculty of Comupter Science and Information Technology

Bibliografia

• [1] A. K. Sen. Capability and Well-Being, pp. 30–54. The Quality of Life. Clarendon Press, Oxford, 1993.
• [2] T. Addabbo, M. D. Tommaso, G. Facchinetti. To what extent fuzzy set theory and structural equation modelling can measure functioningss? An application to child well being Materiali di Discussione del Dipartimento di Economia Politica, 468, 2004.
• [3] E. Adamus, P. Klęsk, J. Kłodziejczyk, M. Korzeń, A. Piegat, M. Pluciński. Child well being estimation on data set collected in Zachodniopomorskie district. Metody Informatyki Stosowanej, (4/2010 (25)):5–10, 2010.
• [4] S. Greco, B. Matarazzo, R. Słowiński. Multicriteria Classification by Dominance-Based Rough Set Approach. Methodological Basis of the 4eMka System. available at http://www-idss.cs.put.poznan.pl/, 2000.
• [5] Laboratory of Intelligent Decision Support Systems, Institute of Computing Science, Poznan University of Technology, Poznan, http://www-idss.cs.put.poznan.pl/. 4eMka System - a rule system for multicriteria decision support integrating dominance relation with rough approximation, 2000.
• [6] S. Greco, B. Matarazzo, R. Słowiński. Handling missing values in rough set analysis of multi-attribute and multi-criteria decision problems. In: N.Zhong, A.Skowron and S.Ohsuga (eds.), New Directions in Rough Sets, Data Mining and Granular-Soft Computing Computing (RSFDGrC’99), Lecture Notes in Artificial Intelligence, Springer-Verlag, Berlin, 1711:146–157, 1999.
• [7] D. Rubin. Inference on missing Data. Biometrika, 63:581, 1976.
• [8] S. Greco, B. Matarazzo, R. Słowiński. The use of rough sets and fuzzy sets in MCDM. In: Advances in Multiple Criteria Decision Making, edited by T.Gal, T. Hanne and T. Stewart. Dordrecht, Boston: Kluwer Academic Publishers, 14:14.1–14.59, 1999.
• [9] S. Greco, B. Matarazzo, R. Słowiński, Stefanowski. An algorithm for induction of decision rules consistent with the dominance principle. Proc. RSCTC’2000 Conference, Banff, 2000.
• [10] J. Grzymala-Busse. LERS - a system for learning from examples based on rough sets. Intelligent Decision Support. Handbook of Applications and Advances of the Rough Sets Theory, Kluwer Academic Publishers Slowinski R., (ed.), Dordrecht, 3-18, 1992.