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Handling extreme imbalanced multi-class data with MCDO-BR: a diversity-based synthetic over-sampling technique
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| Published in: | International Journal of Data Science and Analytics |
|---|---|
| Format: | Online Article RSS Article |
| Published: |
2026
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| Subjects: | |
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| _version_ | 1870116637832642560 |
|---|---|
| collection | WordPress RSS FRELIP Feed Integration |
| container_title | International Journal of Data Science and Analytics |
| description | |
| discipline_display | Big data and data science |
| discipline_facet | Big data and data science |
| format | Online Article RSS Article |
| genre | Journal Article |
| id | rss_article:100852 |
| institution | FRELIP |
| journal_source_facet | International Journal of Data Science and Analytics |
| last_indexed | 2026-07-08T03:43:26.021Z |
| publishDate | 2026 |
| publishDateSort | 2026 |
| record_format | rss_article |
| spellingShingle | Handling extreme imbalanced multi-class data with MCDO-BR: a diversity-based synthetic over-sampling technique Big data and data science General Big data and data science |
| sub_discipline_display | General |
| sub_discipline_facet | General |
| subject_display | Big data and data science General Big data and data science |
| subject_facet | Big data and data science General Big data and data science |
| title | Handling extreme imbalanced multi-class data with MCDO-BR: a diversity-based synthetic over-sampling technique |
| title_alt | Manejo de datos multiclase extremadamente desequilibrados con MCDO-BR: una técnica de sobremuestreo sintético basada en diversidad Gestion des données multi-classes extrêmement déséquilibrées avec MCDO-BR : une technique de sur-échantillonnage synthétique basée sur la diversité Lidando com dados multiclasse extremamente desbalanceados com MCDO-BR: uma técnica de superamostragem sintética baseada em diversidade |
| title_auth | Handling extreme imbalanced multi-class data with MCDO-BR: a diversity-based synthetic over-sampling technique |
| title_es_txt | Manejo de datos multiclase extremadamente desequilibrados con MCDO-BR: una técnica de sobremuestreo sintético basada en diversidad |
| title_fr_txt | Gestion des données multi-classes extrêmement déséquilibrées avec MCDO-BR : une technique de sur-échantillonnage synthétique basée sur la diversité |
| title_full | Handling extreme imbalanced multi-class data with MCDO-BR: a diversity-based synthetic over-sampling technique |
| title_fullStr | Handling extreme imbalanced multi-class data with MCDO-BR: a diversity-based synthetic over-sampling technique |
| title_full_unstemmed | Handling extreme imbalanced multi-class data with MCDO-BR: a diversity-based synthetic over-sampling technique |
| title_pt_txt | Lidando com dados multiclasse extremamente desbalanceados com MCDO-BR: uma técnica de superamostragem sintética baseada em diversidade |
| title_short | Handling extreme imbalanced multi-class data with MCDO-BR: a diversity-based synthetic over-sampling technique |
| title_sort | handling extreme imbalanced multi-class data with mcdo-br: a diversity-based synthetic over-sampling technique |
| topic | Big data and data science General Big data and data science |
| url | https://link.springer.com/article/10.1007/s41060-026-01176-9 |