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Feature Selection in High-Dimensional Models via EBIC with Energy Distance Correlation
In this paper, the LASSO method with extended Bayesian information criteria (EBIC) for feature selection in high-dimensional models is studied. We propose the use of the energy distance correlation in place of the ordinary correlation coefficient to measure the dependence of two variables. The energ...
| Autores principales: | , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
MDPI
2022
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9857644/ https://www.ncbi.nlm.nih.gov/pubmed/36673154 http://dx.doi.org/10.3390/e25010014 |