Improving the k-NN method: rough set in edit training set

Rough Set Theory (RST) is a technique for data analysis. In this study, we use RST to improve the performance of k-NN method. The RST is used to edit and reduce the training set. We propose two methods to edit training sets, which are based on the lower and upper approximations. Experimental result...

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Detalles Bibliográficos
Autores principales: Caballero, Yailé, Bello, Rafael, Álvarez, Delia, García, María M., Pizano, Yaimara
Formato: Objeto de conferencia
Lenguaje:Inglés
Publicado: 2006
Materias:
Ciencias Informáticas
data analysis
training sets
Rough Set Theory (RST)
Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/24150
Aporte de:
SEDICI (UNLP) de Universidad Nacional de La Plata
id I19-R120-10915-24150
record_format dspace
institution Universidad Nacional de La Plata
institution_str I-19
repository_str R-120
collection SEDICI (UNLP)
language Inglés
topic Ciencias Informáticas
data analysis
training sets
Rough Set Theory (RST)
spellingShingle Ciencias Informáticas
data analysis
training sets
Rough Set Theory (RST)
Caballero, Yailé
Bello, Rafael
Álvarez, Delia
García, María M.
Pizano, Yaimara
Improving the k-NN method: rough set in edit training set
topic_facet Ciencias Informáticas
data analysis
training sets
Rough Set Theory (RST)
description Rough Set Theory (RST) is a technique for data analysis. In this study, we use RST to improve the performance of k-NN method. The RST is used to edit and reduce the training set. We propose two methods to edit training sets, which are based on the lower and upper approximations. Experimental results show a satisfactory performance of k-NN method using these techniques.
format Objeto de conferencia
Objeto de conferencia
author Caballero, Yailé
Bello, Rafael
Álvarez, Delia
García, María M.
Pizano, Yaimara
author_facet Caballero, Yailé
Bello, Rafael
Álvarez, Delia
García, María M.
Pizano, Yaimara
author_sort Caballero, Yailé
title Improving the k-NN method: rough set in edit training set
title_short Improving the k-NN method: rough set in edit training set
title_full Improving the k-NN method: rough set in edit training set
title_fullStr Improving the k-NN method: rough set in edit training set
title_full_unstemmed Improving the k-NN method: rough set in edit training set
title_sort improving the k-nn method: rough set in edit training set
publishDate 2006
url http://sedici.unlp.edu.ar/handle/10915/24150
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AT alvarezdelia improvingtheknnmethodroughsetinedittrainingset
AT garciamariam improvingtheknnmethodroughsetinedittrainingset
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