Double-hyperbolic undersampling & probabilistic benchmarks
Benchmarks are standards that allow to identify opportunities for improvement among comparable units. The code performs a 2-step estimation of probabilistic benchmarks in noisy data sets: (i) double-hyperbolic undersampling filters the noise of key performance indicators (KPIs), and (ii) relevance vector machines estimate probabilistic benchmarks with the denoised KPIs. The usefulness of the methods is illustrated with an application to a database of nano-finance+.
Citar como
Rolando Gonzales Martinez (2024). Double-hyperbolic undersampling & probabilistic benchmarks (https://www.mathworks.com/matlabcentral/fileexchange/74398-double-hyperbolic-undersampling-probabilistic-benchmarks), MATLAB Central File Exchange. Recuperado .
Compatibilidad con la versión de MATLAB
Compatibilidad con las plataformas
Windows macOS LinuxEtiquetas
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!Descubra Live Editor
Cree scripts con código, salida y texto formateado en un documento ejecutable.
2Hbenchpack
Versión | Publicado | Notas de la versión | |
---|---|---|---|
1.0.0 |