Cargando…
Evaluation of Forensic Data Using Logistic Regression-Based Classification Methods and an R Shiny Implementation
We demonstrate the use of classification methods that are well-suited for forensic toxicology applications. The methods are based on penalized logistic regression, can be employed when separation occurs in a two-class classification setting, and allow for the calculation of likelihood ratios. A case...
Autores principales: | Biosa, Giulia, Giurghita, Diana, Alladio, Eugenio, Vincenti, Marco, Neocleous, Tereza |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7609892/ https://www.ncbi.nlm.nih.gov/pubmed/33195014 http://dx.doi.org/10.3389/fchem.2020.00738 |
Ejemplares similares
-
ShinyKGode: an interactive application for ODE parameter inference using gradient matching
por: Wandy, Joe, et al.
Publicado: (2018) -
Experimental and statistical protocol for the effective validation of chromatographic analytical methods
por: Alladio, Eugenio, et al.
Publicado: (2020) -
The “DOLPHINS” Project: A Low-Cost Real-Time Multivariate Process Control From Large Sensor Arrays Providing Sparse Binary Data
por: Alladio, Eugenio, et al.
Publicado: (2021) -
Effective Search of Triterpenes with Anti-HSV-1 Activity Using a Classification Model by Logistic Regression
por: Ogawa, Keiko, et al.
Publicado: (2021) -
Multivariate statistical approach and machine learning for the evaluation of biogeographical ancestry inference in the forensic field
por: Alladio, Eugenio, et al.
Publicado: (2022)