Close
Metadata

1. Identity statement
Reference TypeConference Paper (Conference Proceedings)
Sitesibgrapi.sid.inpe.br
Holder Codeibi 8JMKD3MGPEW34M/46T9EHH
Identifier8JMKD3MGPEW34M/45D9PFB
Repositorysid.inpe.br/sibgrapi/2021/09.08.17.30
Last Update2021:09.08.17.30.02 (UTC) administrator
Metadata Repositorysid.inpe.br/sibgrapi/2021/09.08.17.30.02
Metadata Last Update2022:09.10.00.16.17 (UTC) administrator
Citation KeyPereiraCostJr:2021:DeImHi
TitleDealing with Imbalanceness in Hierarchical Classification Problems Through Data Resampling
FormatOn-line
Year2021
Access Date2024, May 06
Number of Files1
Size604 KiB
2. Context
Author1 Pereira, Rodolfo Miranda
2 Costa, Yandre Maldonado e Gomes da
3 Jr. , Carlos Nascimento Silla
Affiliation1 Pontifícia Universidade Católica do Paraná (PUCPR) e Instituto Federal do Paraná (IFPR)
2 Universidade Estadual de Maringá (UEM)
3 Pontifícia Universidade Católica do Paraná (PUCPR)
EditorPaiva, Afonso
Menotti, David
Baranoski, Gladimir V. G.
Proença, Hugo Pedro
Junior, Antonio Lopes Apolinario
Papa, João Paulo
Pagliosa, Paulo
dos Santos, Thiago Oliveira
e Sá, Asla Medeiros
da Silveira, Thiago Lopes Trugillo
Brazil, Emilio Vital
Ponti, Moacir A.
Fernandes, Leandro A. F.
Avila, Sandra
e-Mail Addressrodolfomp123@gmail.com
Conference NameConference on Graphics, Patterns and Images, 34 (SIBGRAPI)
Conference LocationGramado, RS, Brazil (virtual)
Date18-22 Oct. 2021
PublisherSociedade Brasileira de Computação
Publisher CityPorto Alegre
Book TitleProceedings
Tertiary TypeMaster's or Doctoral Work
History (UTC)2021-09-08 17:30:02 :: rodolfomp123@gmail.com -> administrator ::
2022-09-10 00:16:17 :: administrator -> :: 2021
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Keywordshierarchical classification
class imbalance
resampling algorithms
AbstractMany important classification problems are imbalanced. Although resampling approaches are a common solution for different types of classification problems, they were still not defined for hierarchical classification problems. The objective of this work is to propose novel resampling approaches to handle the class imbalanceness issue in hierarchical classification problems. Four directions were investigated: (i) The use of classic resampling methods; (ii) A label path conversion strategy; (iii) The design of schemas to use resampling algorithms with local approaches; (iv) The proposal of global resampling algorithms. To show the impacts of the contribution of this work, we have investigated the imbalanceness issue in the COVID-19 identification in chest x-ray images.
Arrangementurlib.net > SDLA > Fonds > SIBGRAPI 2021 > Dealing with Imbalanceness...
doc Directory Contentaccess
source Directory Contentthere are no files
agreement Directory Content
agreement.html 08/09/2021 14:30 1.3 KiB 
4. Conditions of access and use
data URLhttp://urlib.net/ibi/8JMKD3MGPEW34M/45D9PFB
zipped data URLhttp://urlib.net/zip/8JMKD3MGPEW34M/45D9PFB
Languageen
Target FileWTD_SIBGRAPI_2021_Camera_Ready.pdf
User Grouprodolfomp123@gmail.com
Visibilityshown
5. Allied materials
Mirror Repositorysid.inpe.br/banon/2001/03.30.15.38.24
Next Higher Units8JMKD3MGPEW34M/45PQ3RS
Citing Item Listsid.inpe.br/sibgrapi/2021/11.12.11.46 3
sid.inpe.br/banon/2001/03.30.15.38.24 1
Host Collectionsid.inpe.br/banon/2001/03.30.15.38
6. Notes
Empty Fieldsarchivingpolicy archivist area callnumber contenttype copyholder copyright creatorhistory descriptionlevel dissemination documentstage doi edition electronicmailaddress group isbn issn label lineage mark nextedition notes numberofvolumes orcid organization pages parameterlist parentrepositories previousedition previouslowerunit progress project readergroup readpermission resumeid rightsholder schedulinginformation secondarydate secondarykey secondarymark secondarytype serieseditor session shorttitle sponsor subject tertiarymark type url versiontype volume


Close