ENSEMBLE LEARNING ALGORITHMS IN PATTERN RECOGNITION TASKS

dc.contributor.author Kabulov B.M.
dc.contributor.authorAitbayev Y.K.
dc.contributor.authorAmirgaliyev Y.N.
dc.date.accessioned2023-10-26T09:33:35Z
dc.date.available2023-10-26T09:33:35Z
dc.date.issued2017
dc.description.abstractAbstract. There has been growing interest in pattern recognition tasks in the last decade. This is determined by the prevalence of the problems that is being solved in recognizing images and characters, scene analysis, technical and medical diagnostics, signal identification, analysis of expert data, speech recognition, creation of expert and artificial intelligence systems. The article is devoted to the topic of collective decision-making models in automated intellectual systems. The application of such models for pattern recognition problems is being considered. What is meant by the term «collective recognition» is the task of using multiple classifiers, each of which will decide on the class of one entity with the subsequent coordination of their decisions with the help of a certain algorithm.
dc.identifier.citationB.M. Kabulov, Y.K. Aitbayev, Y.N. Amirgaliyev / ENSEMBLE LEARNING ALGORITHMS IN PATTERN RECOGNITION TASKS / СДУ хабаршысы - 2017
dc.identifier.issn2415-8135
dc.identifier.urihttps://repository.sdu.edu.kz/handle/123456789/592
dc.language.isoen
dc.publisherСДУ хабаршысы - 2017
dc.subjectpattern recognition
dc.subjectgroup decisions
dc.subjectcollective analysis
dc.subjectintellectual systems.
dc.subjectСДУ хабаршысы - 2017
dc.subject№2
dc.titleENSEMBLE LEARNING ALGORITHMS IN PATTERN RECOGNITION TASKS
dc.typeArticle
dspace.entity.type

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