Feature Selection using Typical Testors applied to Estimation of Stellar Parameters

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1. Verfasser: José Á. Santos
Format: Artículo científico
Sprache:en
Veröffentlicht: Instituto Politécnico Nacional 2004
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author José Á. Santos
author_facet José Á. Santos
contents Feature Selection using Typical Testors applied to Estimation of Stellar Parameters José Á. Santos Ariel Carrasco José F. Martínez Computación Typical Testors Feature Selection Prediction of Stellar Parameters Logical Combinatorial Pattern Recognition In this paper a comparative analysis of feature selection using typical testors applied on astronomical data, is presented. The comparison is based on the classification efficiency using typical testors as feature selection method against the classification efficiency using Ramirez (2001) method, which uses genetic algorithms. The well-known K-nearest neighbors rule (KNN) was used as classifier. The feature selection based on typical testors was modified to be applied on a prediction problem of a real valued function. The feature selection obtained with typical testors reduces the amount of features in approximately 50% and the classification error index is better than both using the original data and Ramirez´s method. 2004 artículo científico 1405-5546 https://www.redalyc.org/articulo.oa?id=61580103 en http://www.redalyc.org/revista.oa?id=615 Computación y Sistemas application/pdf Instituto Politécnico Nacional Computación y Sistemas (México) Num.1 Vol.8
format Artículo científico
id redalyc_61580103
institution Redalyc
language en
publishDate 2004
publisher Instituto Politécnico Nacional
spellingShingle Feature Selection using Typical Testors applied to Estimation of Stellar Parameters
José Á. Santos
Computación
Typical Testors
Feature Selection
Prediction of Stellar Parameters
Logical Combinatorial Pattern Recognition
Feature Selection using Typical Testors applied to Estimation of Stellar Parameters José Á. Santos Ariel Carrasco José F. Martínez Computación Typical Testors Feature Selection Prediction of Stellar Parameters Logical Combinatorial Pattern Recognition In this paper a comparative analysis of feature selection using typical testors applied on astronomical data, is presented. The comparison is based on the classification efficiency using typical testors as feature selection method against the classification efficiency using Ramirez (2001) method, which uses genetic algorithms. The well-known K-nearest neighbors rule (KNN) was used as classifier. The feature selection based on typical testors was modified to be applied on a prediction problem of a real valued function. The feature selection obtained with typical testors reduces the amount of features in approximately 50% and the classification error index is better than both using the original data and Ramirez´s method. 2004 artículo científico 1405-5546 https://www.redalyc.org/articulo.oa?id=61580103 en http://www.redalyc.org/revista.oa?id=615 Computación y Sistemas application/pdf Instituto Politécnico Nacional Computación y Sistemas (México) Num.1 Vol.8
title Feature Selection using Typical Testors applied to Estimation of Stellar Parameters
topic Computación
Typical Testors
Feature Selection
Prediction of Stellar Parameters
Logical Combinatorial Pattern Recognition
url https://www.redalyc.org/articulo.oa?id=61580103