Cargando…
Robustness of autoencoders for establishing psychometric properties based on small sample sizes: results from a Monte Carlo simulation study and a sports fan curiosity study
BACKGROUND: The principal component analysis (PCA) is known as a multivariate statistical model for reducing dimensions into a representation of principal components. Thus, the PCA is commonly adopted for establishing psychometric properties, i.e., the construct validity. Autoencoder is a neural net...
Autores principales: | Lin, Yen-Kuang, Lee, Chen-Yin, Chen, Chen-Yueh |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
PeerJ Inc.
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9044230/ https://www.ncbi.nlm.nih.gov/pubmed/35494838 http://dx.doi.org/10.7717/peerj-cs.782 |
Ejemplares similares
-
Epidemic monitoring in real-time based on dynamic grid search and Monte Carlo numerical simulation algorithm
por: Chen, Xin, et al.
Publicado: (2023) -
J-score: a robust measure of clustering accuracy
por: Ahmadinejad, Navid, et al.
Publicado: (2023) -
RobOMP: Robust variants of Orthogonal Matching Pursuit for sparse representations
por: Loza, Carlos A.
Publicado: (2019) -
Robust proportional overlapping analysis for feature selection in binary classification within functional genomic experiments
por: Hamraz, Muhammad, et al.
Publicado: (2021) -
Splitting ore from X-ray image based on improved robust concave-point algorithm
por: Wang, Lanhao, et al.
Publicado: (2023)