Cargando…
Area under Precision-Recall Curves for Weighted and Unweighted Data
Precision-recall curves are highly informative about the performance of binary classifiers, and the area under these curves is a popular scalar performance measure for comparing different classifiers. However, for many applications class labels are not provided with absolute certainty, but with some...
Autores principales: | Keilwagen, Jens, Grosse, Ivo, Grau, Jan |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2014
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3961324/ https://www.ncbi.nlm.nih.gov/pubmed/24651729 http://dx.doi.org/10.1371/journal.pone.0092209 |
Ejemplares similares
-
PRROC: computing and visualizing precision-recall and receiver operating characteristic curves in R
por: Grau, Jan, et al.
Publicado: (2015) -
A relationship between the incremental values of area under the ROC curve and of area under the precision-recall curve
por: Zhou, Qian M., et al.
Publicado: (2021) -
A general approach for discriminative de novo motif discovery from high-throughput data
por: Grau, Jan, et al.
Publicado: (2013) -
Approximating the correction of weighted and unweighted orthology and paralogy relations
por: Dondi, Riccardo, et al.
Publicado: (2017) -
Apples and oranges: avoiding different priors in Bayesian DNA sequence analysis
por: Keilwagen, Jens, et al.
Publicado: (2010)