Data classification: Dimensionality reduction using combined and non-combined multidimensional projection techniques

dc.contributorUniversidade Estadual Paulista (Unesp)
dc.date.accessioned2019-10-06T15:32:15Z
dc.date.accessioned2022-12-19T18:29:27Z
dc.date.available2019-10-06T15:32:15Z
dc.date.available2022-12-19T18:29:27Z
dc.date.created2019-10-06T15:32:15Z
dc.date.issued2018-12-13
dc.identifierProceedings - 2018 Brazilian Conference on Intelligent Systems, BRACIS 2018, p. 402-407.
dc.identifierhttp://hdl.handle.net/11449/187310
dc.identifier10.1109/BRACIS.2018.00076
dc.identifier2-s2.0-85060854731
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/5368348
dc.description.abstractDimensionality Reduction is a commonly used method to reduce the number of dimensions of data. In this work, we verified its influence in classification process using combinations of projection techniques as dimensionality reduction algorithms. We also used Naïve Bayes and SMO as classifiers.
dc.languageeng
dc.relationProceedings - 2018 Brazilian Conference on Intelligent Systems, BRACIS 2018
dc.rightsAcesso restrito
dc.sourceScopus
dc.subjectCombination
dc.subjectData Classification
dc.subjectMultidimensional Data Projection
dc.subjectProjection Techniques
dc.titleData classification: Dimensionality reduction using combined and non-combined multidimensional projection techniques
dc.typeActas de congresos


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