Applying a Reference Objects Preselection Algorithm to Real-World Data

The problem of optimal selection of learning objects is investigated. The effectiveness of the previously proposed iterative method for generating sets of relevant precedents is demonstrated on real-world data.

Bibliographic Details

Published in:	Pattern recognition and image analysis Vol. 28; no. 3; pp. 427 - 429
Main Author:	Bondarenko, N. N.
Format:	Journal Article
Language:	English
Published:	Moscow Pleiades Publishing 01.07.2018 Springer Nature B.V
Subjects:	Applied Problems Computer Science Image Processing and Computer Vision Machine learning Pattern Recognition kestimate calculation algorithms algebraic theory of algorithms set of relevant precedents selection of learning objects and brain–computer interface
ISSN:	1054-6618, 1555-6212
Online Access:	Get full text
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