Subtitle:

Książka = Book ; KS/4/2012/P05

Publisher:

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

Place of publishing:

Warszawa

Description:

[5], 45-57 pages ; 21 cm ; Bibliography p. 55-57

Type of object:

Book/Chapter

Abstract:

Computer aided data mining, and in particular methods of clustering, its widely used technique, develop very rapidly nowadays. Basically, clustering is an unsupervised learning technique. However, there is a growing interest in considering the case where there is a partial knowledge on the actual grouping of the objects available. This knowledge may take form of the hints on the co-occurrence of object in the same clusters. In this paper we propose to solve this problem of constrained clustering using the technique of differential evolution (DE). We show the efficiency and usefulness of differential evolution in hard- and soft-constrained clustering tasks. Some practical examples of the clustering problems are examined and results obtained are compared to two variants of a classic clustering technique, the k-means algorithm.

Relation:

Książka = Book

Detailed Resource Type:

Book

Resource Identifier:

oai:rcin.org.pl:205934

Source:

KS-2012-04-P05

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