Co-author(s) :

Aslanyan Levon ; Ryazanov Valery

Abstract:

A problem of classification by precedents in partial precedence models is considered. An algorithm is presented for searching for maximum logical regularities of a class (LRCs) for consistent training tables. A two-level solution scheme of a problem is proposed for finding an optimal decision rule. First, LRCs are obtained by training data, and a mapping of the initial feature descriptions of objects into a space of points of a discrete unit cube is constructed. The objects of the training sample can be divided by a hyperplane in the latter space. It is suggested that a linear decision rule in the latter space that provides the maximum gap, similar to the support vector method, should be used as the decision rule.

Date of publication:

01.09.2014

Identifier:

oai:noad.sci.am:136154

DOI:

10.1134/S1054661814030183

ISSN:

1054-6618

Language:

English

Journal or Publication Title:

Pattern recognition and image analysis

Volume:

24

Number:

3

URL:

Affiliation:

Dorodnicyn Computing Centre, Russian Academy of Sciences, Moscow ; Institute for Informatics and Automation Problems

Country:

Armenia ; Russia

Indexing:

Scopus