An Algorithm for Reselecting a Reference Objects

The problem of optimally choosing a learning object is studied. The definition of essential totality of precedents is given. It is shown that an iterative procedure for generating the essential totality of precedents exists. The algorithm operation is checked on model data.

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Bibliographic Details
Published in:	Pattern recognition and image analysis Vol. 28; no. 4; pp. 684 - 687
Main Author:	Bondarenko, N. N.
Format:	Journal Article
Language:	English
Published:	Moscow Pleiades Publishing 01.10.2018 Springer Nature B.V
Subjects:	Algorithms Computer Science Image Processing and Computer Vision Iterative methods Mathematical Method in Pattern Recognition Pattern Recognition algebraic theory of algorithms algorithm for calculation of estimates selection of learning objects totality of essential precedents
ISSN:	1054-6618, 1555-6212
Online Access:	Get full text
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Summary:	The problem of optimally choosing a learning object is studied. The definition of essential totality of precedents is given. It is shown that an iterative procedure for generating the essential totality of precedents exists. The algorithm operation is checked on model data.
Bibliography:	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14
ISSN:	1054-6618 1555-6212
DOI:	10.1134/S1054661818040053