Cargando…
Standard Decision Boundary in a Support-Domain of Fuzzy Classifier Prediction for the Task of Imbalanced Data Classification
Many real classification problems are characterized by a strong disturbance in a prior probability, which for the most of classification algorithms leads to favoring majority classes. The action most often used to deal with this problem is oversampling of the minority class by the smote algorithm. F...
Autor principal: | Ksieniewicz, Pawel |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7303698/ http://dx.doi.org/10.1007/978-3-030-50423-6_8 |
Ejemplares similares
-
Clustering and Weighted Scoring in Geometric Space Support Vector Machine Ensemble for Highly Imbalanced Data Classification
por: Ksieniewicz, Paweł, et al.
Publicado: (2020) -
Application of Imbalanced Data Classification Quality Metrics as Weighting Methods of the Ensemble Data Stream Classification Algorithms
por: Wegier, Weronika, et al.
Publicado: (2020) -
A Correction Method of a Base Classifier Applied to Imbalanced Data Classification
por: Trajdos, Pawel, et al.
Publicado: (2020) -
Deep Learning-Based Imbalanced Classification With Fuzzy Support Vector Machine
por: Wang, Ke-Fan, et al.
Publicado: (2022) -
Classifying Extremely Imbalanced Data Sets
por: Britsch, M, et al.
Publicado: (2010)