Parzen neural networks: Fundamentals, properties, and an application to forensic anthropology.
Neural Netw
; 97: 137-151, 2018 Jan.
Article
en En
| MEDLINE
| ID: mdl-29096202
ABSTRACT
A novel, unsupervised nonparametric model of multivariate probability density functions (pdf) is introduced, namely the Parzen neural network (PNN). The PNN is intended to overcome the major limitations of traditional (either statistical or neural) pdf estimation techniques. Besides being profitably simple, the PNN turns out to have nice properties in terms of unbiased modeling capability, asymptotic convergence, and efficiency at test time. Several matters pertaining the practical application of the PNN are faced in the paper, too. Experiments are reported, involving (i) synthetic datasets, and (ii) a challenging sex determination task from 1400 scout-view CT-scan images of human crania. Incidentally, the empirical evidence entails also some conclusions of high anthropological relevance.
Palabras clave
Texto completo:
1
Base de datos:
MEDLINE
Asunto principal:
Redes Neurales de la Computación
/
Antropología Forense
Tipo de estudio:
Prognostic_studies
Idioma:
En
Revista:
Neural Netw
Asunto de la revista:
NEUROLOGIA
Año:
2018
Tipo del documento:
Article