Dropout through extended association rule netwoks: A complementary view
Autor(a) principal: | |
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Data de Publicação: | 2020 |
Outros Autores: | , , , |
Tipo de documento: | Artigo de conferência |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://hdl.handle.net/11449/205214 |
Resumo: | Dropout is a critical problem that has been studied by data mining methods. The most widely used algorithm in this context is C4.5. However, the understanding of the reasons why a student dropout is a result of its representation. As C4.5 is a greedy algorithm, it is difficult to visualize, for example, items that are dominants and determinants with respect to a specific class. An alternative is to use association rules (ARs), since they exploit the search space more broadly. However, in the dropout context, few works use them. (Padua et al., 2018) proposed an approach, named ExARN, that structures, prunes and analyzes a set of ARs to build candidate hypotheses. Considering the above, the goal of this work is to treat the dropout problem through ExARN as it provides a complementary view to what is commonly used in the literature, i.e., classification through C4.5. As contributions we have: (a) complementary views are important and, therefore, should be used more often when the focus is to understand the domain, not only classify; (b) the use of ARs through ExARN may reveal interesting correlations that may help to understand the problem of dropping out. |
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Dropout through extended association rule netwoks: A complementary viewAssociation RulesC4.5DropoutNetworkDropout is a critical problem that has been studied by data mining methods. The most widely used algorithm in this context is C4.5. However, the understanding of the reasons why a student dropout is a result of its representation. As C4.5 is a greedy algorithm, it is difficult to visualize, for example, items that are dominants and determinants with respect to a specific class. An alternative is to use association rules (ARs), since they exploit the search space more broadly. However, in the dropout context, few works use them. (Padua et al., 2018) proposed an approach, named ExARN, that structures, prunes and analyzes a set of ARs to build candidate hypotheses. Considering the above, the goal of this work is to treat the dropout problem through ExARN as it provides a complementary view to what is commonly used in the literature, i.e., classification through C4.5. As contributions we have: (a) complementary views are important and, therefore, should be used more often when the focus is to understand the domain, not only classify; (b) the use of ARs through ExARN may reveal interesting correlations that may help to understand the problem of dropping out.Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)Universidade Estadual Paulista (Unesp) Instituto de Geociências e Ciências ExatasUniversidade de São Paulo (USP) Instituto de Ciências Matemáticas e de ComputaçãoUniversidade Estadual Paulista (Unesp) Instituto de Geociências e Ciências ExatasUniversidade Estadual Paulista (Unesp)Universidade de São Paulo (USP)Dall'Agnol, Maicon [UNESP]de Souza, Leandro Rondado [UNESP]de Padua, Renande Carvalho, Veronica OliveiraRezende, Solange Oliveira2021-06-25T10:11:41Z2021-06-25T10:11:41Z2020-01-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObject89-96CSEDU 2020 - Proceedings of the 12th International Conference on Computer Supported Education, v. 1, p. 89-96.http://hdl.handle.net/11449/2052142-s2.0-85091435829Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengCSEDU 2020 - Proceedings of the 12th International Conference on Computer Supported Educationinfo:eu-repo/semantics/openAccess2021-10-23T12:10:51Zoai:repositorio.unesp.br:11449/205214Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-06T00:05:43.638813Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
Dropout through extended association rule netwoks: A complementary view |
title |
Dropout through extended association rule netwoks: A complementary view |
spellingShingle |
Dropout through extended association rule netwoks: A complementary view Dall'Agnol, Maicon [UNESP] Association Rules C4.5 Dropout Network |
title_short |
Dropout through extended association rule netwoks: A complementary view |
title_full |
Dropout through extended association rule netwoks: A complementary view |
title_fullStr |
Dropout through extended association rule netwoks: A complementary view |
title_full_unstemmed |
Dropout through extended association rule netwoks: A complementary view |
title_sort |
Dropout through extended association rule netwoks: A complementary view |
author |
Dall'Agnol, Maicon [UNESP] |
author_facet |
Dall'Agnol, Maicon [UNESP] de Souza, Leandro Rondado [UNESP] de Padua, Renan de Carvalho, Veronica Oliveira Rezende, Solange Oliveira |
author_role |
author |
author2 |
de Souza, Leandro Rondado [UNESP] de Padua, Renan de Carvalho, Veronica Oliveira Rezende, Solange Oliveira |
author2_role |
author author author author |
dc.contributor.none.fl_str_mv |
Universidade Estadual Paulista (Unesp) Universidade de São Paulo (USP) |
dc.contributor.author.fl_str_mv |
Dall'Agnol, Maicon [UNESP] de Souza, Leandro Rondado [UNESP] de Padua, Renan de Carvalho, Veronica Oliveira Rezende, Solange Oliveira |
dc.subject.por.fl_str_mv |
Association Rules C4.5 Dropout Network |
topic |
Association Rules C4.5 Dropout Network |
description |
Dropout is a critical problem that has been studied by data mining methods. The most widely used algorithm in this context is C4.5. However, the understanding of the reasons why a student dropout is a result of its representation. As C4.5 is a greedy algorithm, it is difficult to visualize, for example, items that are dominants and determinants with respect to a specific class. An alternative is to use association rules (ARs), since they exploit the search space more broadly. However, in the dropout context, few works use them. (Padua et al., 2018) proposed an approach, named ExARN, that structures, prunes and analyzes a set of ARs to build candidate hypotheses. Considering the above, the goal of this work is to treat the dropout problem through ExARN as it provides a complementary view to what is commonly used in the literature, i.e., classification through C4.5. As contributions we have: (a) complementary views are important and, therefore, should be used more often when the focus is to understand the domain, not only classify; (b) the use of ARs through ExARN may reveal interesting correlations that may help to understand the problem of dropping out. |
publishDate |
2020 |
dc.date.none.fl_str_mv |
2020-01-01 2021-06-25T10:11:41Z 2021-06-25T10:11:41Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/conferenceObject |
format |
conferenceObject |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
CSEDU 2020 - Proceedings of the 12th International Conference on Computer Supported Education, v. 1, p. 89-96. http://hdl.handle.net/11449/205214 2-s2.0-85091435829 |
identifier_str_mv |
CSEDU 2020 - Proceedings of the 12th International Conference on Computer Supported Education, v. 1, p. 89-96. 2-s2.0-85091435829 |
url |
http://hdl.handle.net/11449/205214 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
CSEDU 2020 - Proceedings of the 12th International Conference on Computer Supported Education |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
89-96 |
dc.source.none.fl_str_mv |
Scopus reponame:Repositório Institucional da UNESP instname:Universidade Estadual Paulista (UNESP) instacron:UNESP |
instname_str |
Universidade Estadual Paulista (UNESP) |
instacron_str |
UNESP |
institution |
UNESP |
reponame_str |
Repositório Institucional da UNESP |
collection |
Repositório Institucional da UNESP |
repository.name.fl_str_mv |
Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP) |
repository.mail.fl_str_mv |
|
_version_ |
1808128241954717696 |