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Listar por palabra clave "Missing data"

Mostrando ítems 1-10 de 10

Clasificación de pacientes de melanoma en grupos etiopatogénicos

Aguerralde Martin, Maider (Universitat Politècnica de València, 2023-01-09)

[ES] Actualmente, el melanoma es el principal causante de muerte por cáncer de la piel. No todos los melanomas se comportan igual, por lo que es de interés disponer de una clasificación de los mismos que permita precisar ...
Cross-validation in PCA models with the element-wise k-fold (ekf) algorithm: Practical Aspects

Camacho Páez, José; Ferrer Riquelme, Alberto José (Elsevier, 2014-02-15)

This is the second paper of a series devoted to provide theoretical and practical results and new algorithms for the selection of the number of Principal Components (PCs) in Principal Component Analysis (PCA) using ...
Cross-validation in PCA models with the element-wise k-fold (ekf) algorithm: theoretical aspects

Camacho Páez, José; Ferrer Riquelme, Alberto José (Wiley, 2012-07)

[EN] Cross-validation has become one of the principal methods to adjust the meta-parameters in predictive models. Extensions of the cross-validation idea have been proposed to select the number of components in principal ...
Enabling network inference methods to handle missing data and outliers

Folch-Fortuny, Abel; Fernández Villaverde, Alejandro; Ferrer Riquelme, Alberto José; Rodríguez Banga, Julio (BioMed Central, 2015-09-03)

[EN] Background: The inference of complex networks from data is a challenging problem in biological sciences, as well as in a wide range of disciplines such as chemistry, technology, economics, or sociology. The quantity ...
Extremely missing numerical data in Electronic Health Records for machine learning can be managed through simple imputation methods considering informative missingness: A comparative of solutions in a COVID-19 mortality case study

Ferri-Borredà, Pablo; Romero-Garcia, Nekane; Badenes, Rafael; Lora-Pablos, David; García Morales, Teresa; Gómez de la Cámara, Agustín; Garcia-Gomez, Juan M.; Sáez Silvestre, Carlos (Elsevier, 2023-12)

[EN] Background and objective: Reusing Electronic Health Records (EHRs) for Machine Learning (ML) leads on many occasions to extremely incomplete and sparse tabular datasets, which can hinder the model development processes ...
Missing Data Imputation Toolbox for MATLAB

Folch Fortuny, Abel; Arteaga Moreno, Francisco Javier; Ferrer, Alberto (Elsevier, 2016-03-15)

[EN] Here we introduce a graphical user-friendly interface to deal with missing values called Missing Data Imputation (MDI) Toolbox. This MATLAB toolbox allows imputing missing values, following missing completely at random ...
On Recovering Missing Ground Penetrating Radar Traces by Statistical Interpolation Methods

Safont Armero, Gonzalo; Salazar Afanador, Addisson; Rodriguez, Alberto; Vergara Domínguez, Luís (MDPI, 2014-08-14)

Missing traces in ground penetrating radar (GPR) B-scans (radargrams) may appear because of limited scanning resolution, failures during the acquisition process or the lack of accessibility to some areas under test. Four ...
PCA model building with missing data: New proposals and a comparative study

Folch-Fortuny, Abel; ARTEAGA MORENO, FRANCISCO JAVIER; Ferrer Riquelme, Alberto José (Elsevier, 2015-08-15)

[EN] This paper introduces new methods for building principal component analysis (PCA) models with missing data: projection to the model plane (PMP), known data regression (KDR), KDR with principal component regression ...
PLS model building with missing data: New algorithms and a comparative study

Folch-Fortuny, Abel; Arteaga, Francisco; Ferrer, Alberto (John Wiley & Sons, 2017-07)

[EN] New algorithms to deal with missing values in predictive modelling are presented in this article. Specifically, 2 trimmed scores regression adaptations are proposed, one from principal component analysis model building ...
Using latent features for short-term person re-identification with RGB-D cameras

Oliver Moll, Javier; Albiol Colomer, Alberto; Albiol Colomer, Antonio José; Mossi García, José Manuel (Springer Verlag (Germany), 2016-05)

This paper presents a system for people re-identification in uncontrolled scenarios using RGB-depth cameras. Compared to conventional RGB cameras, the use of depth information greatly simplifies the tasks of segmentation ...