Caricamento...
Cross-validation pitfalls when selecting and assessing regression and classification models
BACKGROUND: We address the problem of selecting and assessing classification and regression models using cross-validation. Current state-of-the-art methods can yield models with high variance, rendering them unsuitable for a number of practical applications including QSAR. In this paper we describe...
Salvato in:
| Autori principali: | , , , |
|---|---|
| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
Springer International Publishing
2014
|
| Soggetti: | |
| Accesso online: | https://ncbi.nlm.nih.gov/pmc/articles/PMC3994246/ https://ncbi.nlm.nih.gov/pubmed/24678909 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1186/1758-2946-6-10 |
| Tags: |
Aggiungi Tag
Nessun Tag, puoi essere il primo ad aggiungerne! !
|