Clasificacion automática simbólica por medio de algoritmos genéticos
This paper presents a variant in the methods for clustering: a genetic algorithm for clustering through the tools of symbolic data analysis. Their implementation avoids the troubles of clustering classical methods: local minima and dependence of data types: numerical vectors (continuous data type)....
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Universidad de Costa Rica
2010-04-01
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Series: | Revista de Matemática: Teoría y Aplicaciones |
Online Access: | https://revistas.ucr.ac.cr/index.php/matematica/article/view/307 |
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doaj-147b489529754c6ab8af9f1ed922f4dd2020-11-25T02:16:04ZspaUniversidad de Costa RicaRevista de Matemática: Teoría y Aplicaciones2215-33732010-04-0116228329210.15517/rmta.v16i2.307292Clasificacion automática simbólica por medio de algoritmos genéticosFabio Fernández-Jiménez0Alex Murillo Fernández1Universidad de Costa Rica, Escuela de MatemáticaUniversidad de Costa Rica, Escuela de MatemáticaThis paper presents a variant in the methods for clustering: a genetic algorithm for clustering through the tools of symbolic data analysis. Their implementation avoids the troubles of clustering classical methods: local minima and dependence of data types: numerical vectors (continuous data type). The proposed method was programmed in MatLab R and it uses an interesting operator of encoding. We compare the clusters by their intra-clusters inertia. We used the following measures for symbolic data types: Ichino-Yaguchi dissimilarity measure, Gowda-Diday dissimilarity measure, Euclidean distance and Hausdorff distance.https://revistas.ucr.ac.cr/index.php/matematica/article/view/307 |
collection |
DOAJ |
language |
Spanish |
format |
Article |
sources |
DOAJ |
author |
Fabio Fernández-Jiménez Alex Murillo Fernández |
spellingShingle |
Fabio Fernández-Jiménez Alex Murillo Fernández Clasificacion automática simbólica por medio de algoritmos genéticos Revista de Matemática: Teoría y Aplicaciones |
author_facet |
Fabio Fernández-Jiménez Alex Murillo Fernández |
author_sort |
Fabio Fernández-Jiménez |
title |
Clasificacion automática simbólica por medio de algoritmos genéticos |
title_short |
Clasificacion automática simbólica por medio de algoritmos genéticos |
title_full |
Clasificacion automática simbólica por medio de algoritmos genéticos |
title_fullStr |
Clasificacion automática simbólica por medio de algoritmos genéticos |
title_full_unstemmed |
Clasificacion automática simbólica por medio de algoritmos genéticos |
title_sort |
clasificacion automática simbólica por medio de algoritmos genéticos |
publisher |
Universidad de Costa Rica |
series |
Revista de Matemática: Teoría y Aplicaciones |
issn |
2215-3373 |
publishDate |
2010-04-01 |
description |
This paper presents a variant in the methods for clustering: a genetic algorithm for
clustering through the tools of symbolic data analysis. Their implementation avoids
the troubles of clustering classical methods: local minima and dependence of data
types: numerical vectors (continuous data type).
The proposed method was programmed in MatLab R and it uses an interesting
operator of encoding. We compare the clusters by their intra-clusters inertia. We used
the following measures for symbolic data types: Ichino-Yaguchi dissimilarity measure,
Gowda-Diday dissimilarity measure, Euclidean distance and Hausdorff distance. |
url |
https://revistas.ucr.ac.cr/index.php/matematica/article/view/307 |
work_keys_str_mv |
AT fabiofernandezjimenez clasificacionautomaticasimbolicapormediodealgoritmosgeneticos AT alexmurillofernandez clasificacionautomaticasimbolicapormediodealgoritmosgeneticos |
_version_ |
1724892985364054016 |