Համահեղինակ(ներ):

Ryazanov Valery ; Aslanyan Levon ; Sahakyan Hasmik

Ամփոփում:

The construction of a two-level decision scheme for recognition problems with many classes is proposed that is based on the development of the error-correcting output codes (ЕСОС) method. In the “classical” ЕСОС, a large number of partitions of the original classes into two macroclasses are constructed. Each macroclass is a union of some original classes. Each macroclass is assigned either 0 or 1. As a result, each original class is defined by a row of 0 and 1 (the stage of encoding) and a coding matrix is constructed. The stage of classification of an arbitrary new object consists in the solution of each dichotomic problem and application of a special decision rule (the stage of decoding). In this paper, new methods for weighting and taking into account codewords, modifying decision rules, and searching for locally optimal dichotomies are proposed, and various quality criteria for classification and the cases of extension of a codeword are considered.

Հրատարակիչ:

Springer

Ընդունման ամսաթիվը:

27.01.2019

Հրատարակման ամսաթիվ:

18.09.2019

Նույնականացուցիչ:

oai:noad.sci.am:136159

DOI:

10.1134/S1054661819030246

ISSN:

1054-6618

Լեզու:

English

Ամսագրի կամ հրապարակման վերնագիր:

Pattern Recognition and Image Analysis volume

Հատոր:

29

Համար:

3

URL:

Կազմակերպության անվանում:

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

Երկիր:

Armenia ; Russia

Ինդեքսավորում:

Scopus