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Dynamic Classifier Selection for Data with Skewed Class Distribution Using Imbalance Ratio and Euclidean Distance
Imbalanced data analysis remains one of the critical challenges in machine learning. This work aims to adapt the concept of Dynamic Classifier Selection (dcs) to the pattern classification task with the skewed class distribution. Two methods, using the similarity (distance) to the reference instance...
| Autores principales: | , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
2020
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7303765/ http://dx.doi.org/10.1007/978-3-030-50423-6_5 |