Cargando…
On the Performance of Oversampling Techniques for Class Imbalance Problems
Although over 90 oversampling approaches have been developed in the imbalance learning domain, most of the empirical study and application work are still based on the “classical” resampling techniques. In this paper, several experiments on 19 benchmark datasets are set up to study the efficiency of...
Autores principales: | Kong, Jiawen, Rios, Thiago, Kowalczyk, Wojtek, Menzel, Stefan, Bäck, Thomas |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7206329/ http://dx.doi.org/10.1007/978-3-030-47436-2_7 |
Ejemplares similares
-
An oversampling method for multi-class imbalanced data based on composite weights
por: Deng, Mingyang, et al.
Publicado: (2021) -
An Elastic Self-Adjusting Technique for Rare-Class Synthetic Oversampling Based on Cluster Distortion Minimization in Data Stream
por: Fatlawi, Hayder K., et al.
Publicado: (2023) -
Evolutionary Mahalanobis Distance-Based Oversampling for Multi-Class Imbalanced Data Classification
por: Yao, Leehter, et al.
Publicado: (2021) -
Network intrusion detection using oversampling technique and machine learning algorithms
por: Ahmed, Hafiza Anisa, et al.
Publicado: (2022) -
Detecting Hypoglycemia Incidents Reported in Patients’ Secure Messages: Using Cost-Sensitive Learning and Oversampling to Reduce Data Imbalance
por: Chen, Jinying, et al.
Publicado: (2019)