Performance of Classification Algorithms Under Class Imbalance: Simulation and Real-World Evidence
Class imbalance is a persistent challenge in machine learning, particularly in high-stakes applications such as medical diagnostics, bioinformatics, and fraud detection, where the minority class often represents critical cases. While prior research has examined the effect of imbalance on classifier...
Guardado en:
| Autores principales: | , , , , , , |
|---|---|
| Formato: | Artículo |
| Lenguaje: | inglés |
| Publicado: |
2025
|
| Acceso en línea: | Enlace permanente (DOI o Handle) Enlace permanente (DOI o Handle) |
| Etiquetas: |
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares: Performance of Classification Algorithms Under Class Imbalance: Simulation and Real-World Evidence
- A new class of median estimators using auxiliary information under PPS sampling: theoretical properties and empirical evaluation
- A Novel Family of CDF Estimators Under PPS Sampling: Computational, Theoretical, and Applied Perspectives
- Research data and reproducibility records for "Class–Source Confounding and Architecture-Selection Instability under Domain Shift: A Multi-Source Benchmark for Maize Disease and Pest Image Classification"
- Classification Model Based on Chatbot and Unsupervised Algorithms to Determine Psychological Intervention Programs in Peruvian University Students
- Daily Crude Oil Prices Forecasting Using a Novel Hybrid Time Series Technique
- Classification