Please use this identifier to cite or link to this item:
https://dspace.ctu.edu.vn/jspui/handle/123456789/38430
Title: | A boosting classification approach based on som |
Authors: | Nguyên, Hoa Dinh |
Keywords: | Self organizing map Learning vector quantization Adaptive boosting Weighted majority voting |
Issue Date: | 2020 |
Series/Report no.: | Tạp chí Khoa học Công nghệ Thông tin và Truyền thông;Số 02(CS.01) .- Tr.15-20 |
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. |
URI: | https://dspace.ctu.edu.vn/jspui/handle/123456789/38430 |
ISSN: | 2525-2224 |
Appears in Collections: | Khoa học Công nghệ Thông tin và Truyền thông |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
_file_ Restricted Access | 1.95 MB | Adobe PDF | ||
Your IP: 3.147.48.226 |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.