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https://dspace.ctu.edu.vn/jspui/handle/123456789/38430
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Nguyên, Hoa Dinh | - |
dc.date.accessioned | 2020-10-29T08:13:19Z | - |
dc.date.available | 2020-10-29T08:13:19Z | - |
dc.date.issued | 2020 | - |
dc.identifier.issn | 2525-2224 | - |
dc.identifier.uri | https://dspace.ctu.edu.vn/jspui/handle/123456789/38430 | - |
dc.description.abstract | Self-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.iso | en | vi_VN |
dc.relation.ispartofseries | Tạp chí Khoa học Công nghệ Thông tin và Truyền thông;Số 02(CS.01) .- Tr.15-20 | - |
dc.subject | Self organizing map | vi_VN |
dc.subject | Learning vector quantization | vi_VN |
dc.subject | Adaptive boosting | vi_VN |
dc.subject | Weighted majority voting | vi_VN |
dc.title | A boosting classification approach based on som | vi_VN |
dc.type | Article | vi_VN |
Appears in Collections: | Khoa học Công nghệ Thông tin và Truyền thông |
Files in This Item:
File | Description | Size | Format | |
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_file_ Restricted Access | 1.95 MB | Adobe PDF | ||
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