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Wyświetlanie 1-2 z 2
Tytuł:
Generation of reducts and rules in multi-attribute and multi-criteria classification
Autorzy:
Susmaga, R.
Słowiński, R.
Greco, S.
Matarazzo, B.
Powiązania:
https://bibliotekanauki.pl/articles/205913.pdf
Data publikacji:
2000
Wydawca:
Polska Akademia Nauk. Instytut Badań Systemowych PAN
Tematy:
decision rules
dominance relation
intelligent information systems
multi-attribute and multi-criteria classification
reducts of attributes and criteria
rough sets theory
Opis:
The paper addresses the problem of analysing information tables which contain objects described by both attributes and criteria, i.e. attributes with preference-ordered scales. The objects contained in those tables, representing exemplary decisions made by a decision maker or a domain expert, are usually classified into one of several classes that are also often preference-ordered. Analysis of such data using the classic rough set methodology may produce improper results, as the original rough set approach is not able to discover inconsistencies originating from consideration of typical criteria, like e.g. product quality, market share or debt ratio. The paper presents the framework for the analysis of both attributes and criteria and a very promising algorithm for generating reducts. The algorithm presented is evaluated in an experiment with real-life data sets and its results are compared to those by two other reduct generating algorithms.
Źródło:
Control and Cybernetics; 2000, 29, 4; 969-988
0324-8569
Pojawia się w:
Control and Cybernetics
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Rough set based processing of inconsistent information in decision analysis
Autorzy:
Słowiński, R.
Stefanowski, J.
Greco, S.
Matarazzo, B.
Powiązania:
https://bibliotekanauki.pl/articles/206765.pdf
Data publikacji:
2000
Wydawca:
Polska Akademia Nauk. Instytut Badań Systemowych PAN
Tematy:
klasyfikacja
kombinatoryka
teoria decyzji
teoria gier
classification
decision analysis
knowledge based systems
multi-criteria decision analysis
rough sets
rule induction
Opis:
Inconsistent information is one of main difficulties in the explanation and recommendation tasks of decision analysis. We distinguish two kinds of such information inconsistencies : the first is related to indiscernibility of objects described by attributes defined in nominal or ordinal scales, and the other follows from violation of the dominance principle among attributes defined on preference ordered ordinal or cardinal scales, i.e. among criteria. In this paper we discuss how these two kinds of inconsistencies are handled by a new approach based on the rough sets theory. Combination of this theory with inductive learning techniques leads to generation of decision rules from rough approximations of decision classes. Particular attention is paid to numerical attribute scales and preference-ordered scales of criteria, and their influence on the syntax of induced decision rules.
Źródło:
Control and Cybernetics; 2000, 29, 1; 379-404
0324-8569
Pojawia się w:
Control and Cybernetics
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-2 z 2

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