Abstract:

Experimental investigations of various dichotomous classification algorithms are carried out. Dichotomous classification, or Error-Correcting Output Codes (ECOCs) classification, is based on the construction of a binary code matrix. The rows of the matrix contain unique codewords of classes, and columns are called dichotomies. A dichotomous classification consists of two stages: coding (construction of a code matrix) and decoding, making a decision on the correspondence of an object to a class by analyzing the code matrix. In this study, an experimental comparison of newly proposed methods for constructing dichotomies and a comparison of different approaches to decoding by the available code matrix are proposed. Preliminary experiments show the prospects of proposed methods.

Publisher:

Springer

Date submitted:

17 December 2019

Date accepted:

03 February 2020

Date modified:

03 February 2020

Date of publication:

15 September 2020

Identifier:

oai:noad.sci.am:136094

DOI:

10.1134/S105466182003030X

Journal or Publication Title:

Pattern Recognition and Image Analysis

Volume:

30

Number:

3

URL:

Additional Information:

This study was supported by the Russian Foundation for Basic Research, project nos. 18-51-05011 Arm_a, 17-01-00634, and 18-29-03151.

Affiliation:

Dorodnitsyn Computing Centre, Federal Research Center Computer Science and Control, Russian Academy of Sciences ; Moscow Institute of Physics and Technology (State University) ; Institute for Informatics and Automation Problems, National Academy of Science of Armenia

Year:

2020

References:

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