Please use this identifier to cite or link to this item:
https://hdl.handle.net/10316/4486
Title: | A training algorithm for classification of high-dimensional data | Authors: | Vieira, Armando Barradas, Nuno |
Keywords: | Classification; Learning vector quantization; Hidden layer learning vector quantization; Feature extraction; Rutherford backscattering | Issue Date: | 2003 | Citation: | Neurocomputing. 50:(2003) 461-472 | Abstract: | We propose an algorithm for training multi layer preceptrons (MLP) for classification problems, that we named hidden layer learning vector quantization. It consists of applying learning vector quantization to the last hidden layer of a MLP and it gave very successful results on problems containing a large number of correlated inputs. It was applied with excellent results on classification of Rutherford backscattering spectra and to a benchmark problem of image recognition. | URI: | https://hdl.handle.net/10316/4486 | DOI: | 10.1016/S0925-2312(02)00635-5 | Rights: | openAccess |
Appears in Collections: | FCTUC Física - Artigos em Revistas Internacionais |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
file9cc130d4b8bd4fafa1bdb81bd3f2b60a.pdf | 150.83 kB | Adobe PDF | View/Open |
SCOPUSTM
Citations
19
checked on Oct 14, 2024
WEB OF SCIENCETM
Citations
18
checked on Oct 2, 2024
Page view(s) 20
646
checked on Oct 8, 2024
Download(s)
272
checked on Oct 8, 2024
Google ScholarTM
Check
Altmetric
Altmetric
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.