Subtitle:

Książka = Book ; KS/1/2002/P12

Publisher:

Instytut Badań Systemowych. Polska Akademia Nauk ; Systems Research Institute. Polish Academy of Sciences

Place of publishing:

Warszawa

Description:

[1-2], 198-200 pages ; 21 cm ; Bibliography p. 198-200

Type of object:

Book/Chapter

Abstract:

Models and algorithms for effective decision-making in a data-driven environment are discussed. To enhance the quality of the extracted knowledge and decision-making, the data sets are transformed, the knowledge is extracted with multiple algorithms, the impact of the decisions on the modelled process is simulated, and the parameters optimizing process performance are recommended. The applications discussed in this paper differ from most data mining tasks, where the extracted knowledge is used to assign decision values to new objects that have not been included in the training data. For example, in a typical data mining application the equipment fault is recognized based on the failure symptoms. In this paper, a subset of rules is selected from the extracted knowledge to meet the established decision-making criteria. The parameter values represented by the conditions of this set of rules are called a decision signature. A model and algorithms for the selection of the desired parameters ( decision signatures) is presented. The parameters of this model are updated using a framework provided by the learning classifier systems.

Relation:

Książka = Book

Detailed Resource Type:

Book

Resource Identifier:

oai:rcin.org.pl:206695

Source:

KS-2002-01-P12

Language:

eng

Language of abstract:

eng

Rights:

Creative Commons Attribution BY 4.0 license

Terms of use:

Copyright-protected material. [CC BY 4.0] May be used within the scope specified in Creative Commons Attribution BY 4.0 license, full text available at: ; -

Digitizing institution:

Systems Research Institute of the Polish Academy of Sciences

Original in:

Library of Systems Research Institute PAS

Projects co-financed by:

Operational Program Digital Poland, 2014-2020, Measure 2.3: Digital accessibility and usefulness of public sector information; funds from the European Regional Development Fund and national co-financing from the state budget.

Access:

Open