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Adaptivni Sistemi Avtomatičnogo Upravlinnâ
Article . 2017 . Peer-reviewed
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Adaptivni Sistemi Avtomatičnogo Upravlinnâ
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Adaptivni Sistemi Avtomatičnogo Upravlinnâ
Article . 2017
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https://dx.doi.org/10.20535/15...
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МЕТОД МНОГОМЕРНОЙ КЛАССИФИКАЦИИ ОБЪЕКТОВ В ЗАДАЧАХ РАСПОЗНАВАНИЯ ОБРАЗОВ

descriptionPublicationkeyboard_double_arrow_right Article , Other literature type 01 Jun 2017Publisher:Kyiv Politechnic InstituteJournal:Адаптивні системи автоматичного управління, volume 1, pages 170-175 (issn: 1560-8956, eissn: 2522-9575, Copyright policy )

doi: 10.20535/1560-8956.30.2017.117716

МЕТОД МНОГОМЕРНОЙ КЛАССИФИКАЦИИ ОБЪЕКТОВ В ЗАДАЧАХ РАСПОЗНАВАНИЯ ОБРАЗОВ

Abstract

В данной статье предложен эвристический метод многомерной классификации, представляющий собой объединение результатов одномерных классификаций с учетом значимости признаков.

Keywords

T59.5, обучающая выборка, Automation, класс объектов, оператор-классификатор, признаки класса, сигмоидная функция, многомерная классификация

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    popularity
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    influence
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
gold