Please use this identifier to cite or link to this item: https://dspace.ctu.edu.vn/jspui/handle/123456789/38430
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dc.contributor.authorNguyên, Hoa Dinh-
dc.date.accessioned2020-10-29T08:13:19Z-
dc.date.available2020-10-29T08:13:19Z-
dc.date.issued2020-
dc.identifier.issn2525-2224-
dc.identifier.urihttps://dspace.ctu.edu.vn/jspui/handle/123456789/38430-
dc.description.abstractSelf-organizing map (SOM) is well known for its ability to visualize and reduce the dimension of the data. It has been a usefi.ll unsupervised tool for clustering problems for years. In this paper, a new classification framework based on SOM is introduced. In this approach, SOM is combined with the learning vector quanti/ation (LVQ) to form a modified version of the SOM classifier, SOM-LVQ.vi_VN
dc.language.isoenvi_VN
dc.relation.ispartofseriesTạp chí Khoa học Công nghệ Thông tin và Truyền thông;Số 02(CS.01) .- Tr.15-20-
dc.subjectSelf organizing mapvi_VN
dc.subjectLearning vector quantizationvi_VN
dc.subjectAdaptive boostingvi_VN
dc.subjectWeighted majority votingvi_VN
dc.titleA boosting classification approach based on somvi_VN
dc.typeArticlevi_VN
Appears in Collections:Khoa học Công nghệ Thông tin và Truyền thông

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