A self-generating prototype method based on information entropy used for condensing data in classification tasks

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dc.contributor.authorManastarla A.
dc.contributor.authorSilva L.A.
dc.date.accessioned2024-03-12T23:54:43Z
dc.date.available2024-03-12T23:54:43Z
dc.date.issued2019
dc.description.abstract© 2019, Springer Nature Switzerland AG.This paper presents a new self-generating prototype method based on information entropy to reduce the size of training datasets. The method accelerates the classifier training time without significantly decreasing the quality in the data classification task. The effectiveness of the proposed method is compared to the K-nearest neighbour classifier (kNN) and the genetic algorithm prototype selection (GA). kNN is a benchmark method used for data classification tasks, while GA is a prototype selection method that provides competitive optimisation of accuracy and the data reduction ratio. Considering thirty different public datasets, the results of the comparisons demonstrate that the proposed method outperforms kNN when using the original training set as well as the reduced training set obtained via GA prototype selection.
dc.description.firstpage195
dc.description.lastpage207
dc.description.volume11871 LNCS
dc.identifier.doi10.1007/978-3-030-33607-3_22
dc.identifier.issn1611-3349
dc.identifier.urihttps://dspace.mackenzie.br/handle/10899/35350
dc.relation.ispartofLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
dc.rightsAcesso Restrito
dc.subject.otherlanguageData classification
dc.subject.otherlanguageData reduction
dc.subject.otherlanguageGenetic Algorithm (GA)
dc.subject.otherlanguagePrototype Selection (PS)
dc.titleA self-generating prototype method based on information entropy used for condensing data in classification tasks
dc.typeArtigo de evento
local.scopus.citations0
local.scopus.eid2-s2.0-85076635626
local.scopus.subjectClassification tasks
local.scopus.subjectClassifier training
local.scopus.subjectData classification
local.scopus.subjectInformation entropy
local.scopus.subjectK-nearest neighbours
local.scopus.subjectPrototype selection
local.scopus.subjectReduced training sets
local.scopus.subjectTraining data sets
local.scopus.updated2024-05-01
local.scopus.urlhttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85076635626&origin=inward
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