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Wyświetlanie 1-7 z 7
Tytuł:
Handling the description noise using an attribute value ontology
Autorzy:
Łukaszewski, T.
Józefowska, J.
Ławrynowicz, A.
Józefowski, Ł.
Powiązania:
https://bibliotekanauki.pl/articles/206376.pdf
Data publikacji:
2011
Wydawca:
Polska Akademia Nauk. Instytut Badań Systemowych PAN
Tematy:
imprecise descriptions
attribute noise
ontology
naďve Bayesian classifier
Opis:
The quality of any classifier depends on a number of factors, including the quality of training data. In real-world scenarios, data are often noisy. One reason for noisy data (erroneous values) is in the representation language, insufficient to model different levels of knowledge granularity. In this paper, to address the problem of such description noise, we propose a novel extension of the na've Bayesian classifier by an attribute value ontology (AVO). In the proposed approach, every attribute is a hierarchy of concepts from the domain knowledge base. In this way an example is described either very precisely (using a concept from the low-level of the hierarchy) or, when it is not possible, in a more general way (using a concept from higher levels of the hierarchy). Our general strategy is to classify a new example using training examples described in the same way or more precisely at lower levels of knowledge granularity. Hence, the hierarchy introduces a bias which in effect can contribute to improvement of a classification.
Źródło:
Control and Cybernetics; 2011, 40, 2; 275-292
0324-8569
Pojawia się w:
Control and Cybernetics
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
A multiple attribute group decision making method based on generalized interwal-valued trapezoidal fuzzy numbers
Autorzy:
Liu, P.
Wang, Y.
Powiązania:
https://bibliotekanauki.pl/articles/205631.pdf
Data publikacji:
2011
Wydawca:
Polska Akademia Nauk. Instytut Badań Systemowych PAN
Tematy:
interval-valued fuzzy number
grey correlative coefficient
multiple attribute group decision making
Opis:
A ranking approach based on grey correlative coefficient is presented to solve the multiple attribute decision making problems in which the attribute values and the weights take the form of the generalized interval-valued trapezoidal fuzzy number (GIYTFN). Firstly, the concept and the calculation rules of GIYTFN are introduced, the distance of GIYTFN is proposed. Secondly, the method of linguistic terms transformed into GIYTFN and the normalization method of GIYTFN is illustrated, and a grey relational decision making method based on the GIYTFN is presented in detail. The alternatives are ranked based on the grey correlative coefficient. Finally, an illustrative example is given to show the effectiveness of this method and the decision making steps.
Źródło:
Control and Cybernetics; 2011, 40, 1; 163-184
0324-8569
Pojawia się w:
Control and Cybernetics
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Hybrid approach to supporting decision making processes in companies
Autorzy:
Pietruszkiewicz, W.
Twardochleb, M.
Roszkowski, M.
Powiązania:
https://bibliotekanauki.pl/articles/205657.pdf
Data publikacji:
2011
Wydawca:
Polska Akademia Nauk. Instytut Badań Systemowych PAN
Tematy:
data mining
cascade optimization hybrid
parallel classification hybrid
hybrid multicomponent attribute selection
Opis:
This article presents the advantages of hybrid approach to the support decision making by analyzing three areas of business decision problems, solved by combination of well-known algorithms into the new hybrid constructions: cascade optimization hybrid, parallel classification hybrid and hybrid multicomponent attribute selection. Each of them solved a different problem: the cascade optimization hybrid allowed for finding an extreme of a composite objective function, the parallel classification hybrid was used to choose a proper class through voting, the multicomponent attribute selection robustly chose significant decision variables. A hybrid approach to the problem of supporting the decision making processes is more effective than using each of the component methods alone, even for the sophisticated ones. A combination of several methods with different characteristics and performance makes it possible to take advantages of their strong sides and simultaneously eliminate the weak ones, resulting in a better computational support of decision making.
Źródło:
Control and Cybernetics; 2011, 40, 1; 125-143
0324-8569
Pojawia się w:
Control and Cybernetics
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Attribute-oriented denazification of fuzzy database tuples with categorical entries
Autorzy:
Angryk, R. A.
Powiązania:
https://bibliotekanauki.pl/articles/970948.pdf
Data publikacji:
2009
Wydawca:
Polska Akademia Nauk. Instytut Badań Systemowych PAN
Tematy:
defuzzification of fuzzy tuples
non-atomic categorical data entries
attribute-oriented induction
fuzzy databases
fuzzy similarity relation
Opis:
We are investigating the ability to data mine fuzzy tuples, which are often utilized to represent uncertainty about the registered information. We discuss different aspects of fuzzy databases and comment on practical advantages of the model we utilized in our research. Motivated by a well known technique called Attribute-Oriented Induction, which has been developed for summarization of ordinary relational databases, we propose a new heuristic algorithm, allowing attribute-oriented defuzzification of fuzzy database tuples to the form acceptable for many regular (i.e. atomic values based) data mining algorithms. Significant advantages of our approach to defuzzification of fuzzy database tuples include: (1) its intuitive character of fuzzy tuples' interpretation, (2) a unique capability of incorporating background knowledge, implicitly stored in the fuzzy database models in the form of fuzzy similarity relation, directly into the imprecise data interpretation process, (3) transformation of fuzzy tuples to a format easy to process by regular data mining algorithms, and (4) a good scalability for time-efficient treatment of large datasets containing non-atomic, categorical data entries.
Źródło:
Control and Cybernetics; 2009, 38, 2; 419-453
0324-8569
Pojawia się w:
Control and Cybernetics
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
An improved comparison of three rough set approaches to missing attribute values
Autorzy:
Grzymala-Busse, J. W.
Grzymala-Busse, W. J.
Hippe, Z. S.
Rząsa, W.
Powiązania:
https://bibliotekanauki.pl/articles/969797.pdf
Data publikacji:
2010
Wydawca:
Polska Akademia Nauk. Instytut Badań Systemowych PAN
Tematy:
incomplete data sets
missing attribute values
approximations for incomplete data
LERS data mining system
MLEM2 algorithm
Opis:
In a previous paper three types of missing attribute values: lost values, attribute-concept values and "do not care" conditions were compared using six data sets. Since previous experimental results were affected by large variances due to conducting experiments on different versions of a given data set, we conducted new experiments, using the same pattern of missing attribute values for all three types of missing attribute values and for both certain and possible rules. Additionally, in our new experiments, the process of incremental replacing specified values by missing attribute values was terminated when entire rows of the data sets were full of missing attribute values. Finally, we created new, incomplete data sets by replacing the specified values starting from 5% of all attribute values, instead of 10% as in the previous experiments, with an increment of 5% instead of the previous increment of 10%. As a result, it is becoming more clear that the best approach to missing attribute values is based on lost values, with small difference between certain and possible rules, and that the worst approach is based on "do not care" conditions, certain rules. With our improved experimental setup it is also more clear that for a given data set the type of the missing attribute values should be selected individually.
Źródło:
Control and Cybernetics; 2010, 39, 2; 469-486
0324-8569
Pojawia się w:
Control and Cybernetics
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
An approach to multiple attribute decision making with combined weight information in interval-valued intuitionistic fuzzy environment
Autorzy:
Wei, G.
Zhao, X.
Powiązania:
https://bibliotekanauki.pl/articles/206267.pdf
Data publikacji:
2012
Wydawca:
Polska Akademia Nauk. Instytut Badań Systemowych PAN
Tematy:
multiple attribute decision making
interval-valued intuitionistic fuzzy number
interval-valued intuitionistic fuzzy weighted averaging (IIFWA)
weight information
Opis:
With respect to multiple attribute decision making problems with interval-valued intuitionistic fuzzy information, some operational laws of interval-valued intuitionistic fuzzy numbers, score function and accuracy function of interval-valued intuitionistic fuzzy numbers are introduced. A combined optimization model based on the deviation method, by which the attribute weights can be determined, is established. For special situations, in which information about attribute weights is completely unknown, we establish another combined optimization model. By solving this model, we get a simple and exact formula, which can be used to determine the attribute weights. We utilize the interval-valued intuitionistic fuzzy weighted averaging (IIFWA) operator to aggregate the intuitionistic fuzzy information corresponding to each alternative, and then rank the alternatives and select the most desirable one(s) according to the score and accuracy functions. Finally, an illustrative example is given to verify the developed approach and to demonstrate its practicality and effectiveness.
Źródło:
Control and Cybernetics; 2012, 41, 1; 97-112
0324-8569
Pojawia się w:
Control and Cybernetics
Dostawca treści:
Biblioteka Nauki
Artykuł
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
    Wyświetlanie 1-7 z 7

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