Estimate of the Anesthesia Stage in Southern Elephant Seals using WEKA Data Mining Tool

Autores
Zárate, Marcos Daniel; Lewis, Mirtha Noemi
Año de publicación
2016
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Prediction syst ems are techniques that build and study new forecasts through a branch of the artificial intelligence called Machine Lea rning. In this work it is estimate the time that remains anesthetized a southern elephant seal to which you have applied a combination of d rugs (Zoletil®), the fundamental objective of anesthesia is to avoid risky situations to researchers studying this species. To know these times, data mining techniques and classification algorithms are used, particularly algorithms it were compared J48, SM O, Random Tree, NB Tree y Naïve Bayes with data mining tool WEKA and a data set containing the records of 96 individuals undergoing anesthesia procedure. It is concluded that after tests (Random Tree) was the classification algorithm that best responded, with an accuracy of 98.79%.
Fil: Zárate, Marcos Daniel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Centro Nacional Patagónico. Centro para el Estudio de Sistemas Marinos; Argentina
Fil: Lewis, Mirtha Noemi. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Centro Nacional Patagónico. Centro para el Estudio de Sistemas Marinos; Argentina
Materia
Machine Learning
Weka
Anesthesia
Mirounga Leonina
Classification
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/35255
Acceder
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network_name_str CONICET Digital (CONICET)
spelling Estimate of the Anesthesia Stage in Southern Elephant Seals using WEKA Data Mining ToolZárate, Marcos DanielLewis, Mirtha NoemiMachine LearningWekaAnesthesiaMirounga LeoninaClassificationhttps://purl.org/becyt/ford/1.2https://purl.org/becyt/ford/1Prediction syst ems are techniques that build and study new forecasts through a branch of the artificial intelligence called Machine Lea rning. In this work it is estimate the time that remains anesthetized a southern elephant seal to which you have applied a combination of d rugs (Zoletil®), the fundamental objective of anesthesia is to avoid risky situations to researchers studying this species. To know these times, data mining techniques and classification algorithms are used, particularly algorithms it were compared J48, SM O, Random Tree, NB Tree y Naïve Bayes with data mining tool WEKA and a data set containing the records of 96 individuals undergoing anesthesia procedure. It is concluded that after tests (Random Tree) was the classification algorithm that best responded, with an accuracy of 98.79%.Fil: Zárate, Marcos Daniel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Centro Nacional Patagónico. Centro para el Estudio de Sistemas Marinos; ArgentinaFil: Lewis, Mirtha Noemi. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Centro Nacional Patagónico. Centro para el Estudio de Sistemas Marinos; ArgentinaFoundation of Computer Science2016-09info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/35255Zárate, Marcos Daniel; Lewis, Mirtha Noemi; Estimate of the Anesthesia Stage in Southern Elephant Seals using WEKA Data Mining Tool; Foundation of Computer Science; International Journal of Applied Information Systems; 11; 4; 9-2016; 48-52973-93-80892-65-12249-0868CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/http://www.ijais.org/archives/volume11/number4/zarate-2016-ijais-451603.pdfinfo:eu-repo/semantics/altIdentifier/doi/10.5120/ijais2016451603info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T09:35:33Zoai:ri.conicet.gov.ar:11336/35255instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-29 09:35:34.017CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Estimate of the Anesthesia Stage in Southern Elephant Seals using WEKA Data Mining Tool
title Estimate of the Anesthesia Stage in Southern Elephant Seals using WEKA Data Mining Tool
spellingShingle Estimate of the Anesthesia Stage in Southern Elephant Seals using WEKA Data Mining Tool
Zárate, Marcos Daniel
Machine Learning
Weka
Anesthesia
Mirounga Leonina
Classification
title_short Estimate of the Anesthesia Stage in Southern Elephant Seals using WEKA Data Mining Tool
title_full Estimate of the Anesthesia Stage in Southern Elephant Seals using WEKA Data Mining Tool
title_fullStr Estimate of the Anesthesia Stage in Southern Elephant Seals using WEKA Data Mining Tool
title_full_unstemmed Estimate of the Anesthesia Stage in Southern Elephant Seals using WEKA Data Mining Tool
title_sort Estimate of the Anesthesia Stage in Southern Elephant Seals using WEKA Data Mining Tool
dc.creator.none.fl_str_mv Zárate, Marcos Daniel
Lewis, Mirtha Noemi
author Zárate, Marcos Daniel
author_facet Zárate, Marcos Daniel
Lewis, Mirtha Noemi
author_role author
author2 Lewis, Mirtha Noemi
author2_role author
dc.subject.none.fl_str_mv Machine Learning
Weka
Anesthesia
Mirounga Leonina
Classification
topic Machine Learning
Weka
Anesthesia
Mirounga Leonina
Classification
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.2
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv Prediction syst ems are techniques that build and study new forecasts through a branch of the artificial intelligence called Machine Lea rning. In this work it is estimate the time that remains anesthetized a southern elephant seal to which you have applied a combination of d rugs (Zoletil®), the fundamental objective of anesthesia is to avoid risky situations to researchers studying this species. To know these times, data mining techniques and classification algorithms are used, particularly algorithms it were compared J48, SM O, Random Tree, NB Tree y Naïve Bayes with data mining tool WEKA and a data set containing the records of 96 individuals undergoing anesthesia procedure. It is concluded that after tests (Random Tree) was the classification algorithm that best responded, with an accuracy of 98.79%.
Fil: Zárate, Marcos Daniel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Centro Nacional Patagónico. Centro para el Estudio de Sistemas Marinos; Argentina
Fil: Lewis, Mirtha Noemi. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Centro Nacional Patagónico. Centro para el Estudio de Sistemas Marinos; Argentina
description Prediction syst ems are techniques that build and study new forecasts through a branch of the artificial intelligence called Machine Lea rning. In this work it is estimate the time that remains anesthetized a southern elephant seal to which you have applied a combination of d rugs (Zoletil®), the fundamental objective of anesthesia is to avoid risky situations to researchers studying this species. To know these times, data mining techniques and classification algorithms are used, particularly algorithms it were compared J48, SM O, Random Tree, NB Tree y Naïve Bayes with data mining tool WEKA and a data set containing the records of 96 individuals undergoing anesthesia procedure. It is concluded that after tests (Random Tree) was the classification algorithm that best responded, with an accuracy of 98.79%.
publishDate 2016
dc.date.none.fl_str_mv 2016-09
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/35255
Zárate, Marcos Daniel; Lewis, Mirtha Noemi; Estimate of the Anesthesia Stage in Southern Elephant Seals using WEKA Data Mining Tool; Foundation of Computer Science; International Journal of Applied Information Systems; 11; 4; 9-2016; 48-52
973-93-80892-65-1
2249-0868
CONICET Digital
CONICET
url http://hdl.handle.net/11336/35255
identifier_str_mv Zárate, Marcos Daniel; Lewis, Mirtha Noemi; Estimate of the Anesthesia Stage in Southern Elephant Seals using WEKA Data Mining Tool; Foundation of Computer Science; International Journal of Applied Information Systems; 11; 4; 9-2016; 48-52
973-93-80892-65-1
2249-0868
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/http://www.ijais.org/archives/volume11/number4/zarate-2016-ijais-451603.pdf
info:eu-repo/semantics/altIdentifier/doi/10.5120/ijais2016451603
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
application/pdf
dc.publisher.none.fl_str_mv Foundation of Computer Science
publisher.none.fl_str_mv Foundation of Computer Science
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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score 13.070432

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