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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Bibliographische Detailangaben
Veröffentlicht in:	Pattern recognition and image analysis Jg. 28; H. 4; S. 684 - 687
1. Verfasser:	Bondarenko, N. N.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Moscow Pleiades Publishing 01.10.2018 Springer Nature B.V
Schlagworte:	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-Zugang:	Volltext
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Beschreibung
Zusammenfassung:	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.
Bibliographie:	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14
ISSN:	1054-6618 1555-6212
DOI:	10.1134/S1054661818040053