Browsing by author "Quevedo Pérez, José Ramón"

Adapting Decision DAGs for Multipartite Ranking

Quevedo Pérez, José Ramón

; Montañés Roces, Elena

; Luaces Rodríguez, Óscar

; Coz Velasco, Juan José del

(Springer, 2010)

Aggregating independent and dependent models to learn multi-label classifiers

Montañés Roces, Elena

; Quevedo Pérez, José Ramón

; Coz Velasco, Juan José del

(Springer, 2011)

Ajuste de ponderaciones de una rúbrica a partir de juicios de preferencias del docente

Montañés Roces, Elena

; Álvarez Castro, Camino

; Quevedo Pérez, José Ramón

(Dykinson : Universidad Rey Juan Carlos, 2009)

Analyzing sensory data using non-linear preference learning with feature subset selection

Luaces Rodríguez; Fernández Bayón, Gustavo

; Quevedo Pérez, José Ramón

; Díez Peláez, Jorge

; Coz Velasco, Juan José del

; Bahamonde Rionda, Antonio

(Springer, 2004)

Analyzing superstars’ power using support vector machines

Suárez Vázquez, Ana

; Quevedo Pérez, José Ramón

(Springer, 2015-12)

Artificial intelligence techniques point out differences in classification performance between light and standard bovine carcasses

Díez Peláez, Jorge

; Bahamonde Rionda, Antonio

; Alonso González, Jaime

; López, S.; Coz Velasco, Juan José del

; Quevedo Pérez, José Ramón

; Ranilla Pastor, José

; Luaces Rodríguez, Óscar

; Álvarez Fernández, Isabel; Royo Martín, Luis J.; Goyache, Félix (Elsevier, 2003)

Ascertainment of evolutionary processes from the genetic variation associated to each geographic point in a map

Quevedo Pérez, José Ramón

; Fernández-Combarro Álvarez, Elías

; Royo, L.J.; Alvarez, I.; Beja-Pereira, A.; Fernandez, I.; Bahamonde Rionda, Antonio

; Goyache, F. (European Association for Animal Production, 2005-06-05)

Capturing waste collection planning expert knowledge in a fitness function through preference learning

Fernández Díaz, Laura; Fernández Díaz, Miriam; Quevedo Pérez, José Ramón

; Montañés Roces, Elena

(2021)

Code and Data of the article Improving importance estimation in covariate shift for providing accurate prediction error

Fernández Díaz, Laura; González Tomillo, Sara; Montañés Roces, Elena

; Quevedo Pérez, José Ramón

(2022-06-01)

Code and Data of the article Target inductive methods for zero-shot regression

Fernández Díaz, Miriam; Quevedo Pérez, José Ramón

; Montañés Roces, Elena

(2022-06-01)

Collaborative tag recommendation system based on logistic regression

Montañés Roces, Elena

; Quevedo Pérez, José Ramón

; Díaz Rodríguez, Susana Irene

; Ranilla Pastor, José

(2009)

Dependent binary relevance models for multi-label classification

Montañés Roces, Elena

; Senge, Robin; Barranquero Tolosa, José

; Quevedo Pérez, José Ramón

; Coz Díaz, Juan José del

; Hüllermeier, Eyke (2013)

Direct side information learning for zero-shot regression

Fernández Díaz, Miriam; Montañés Roces, Elena

; Quevedo Pérez, José Ramón

(Elsevier, 2023)

Discovering relevancies in very difficult regression problems: applications to sensory data analysis

Díez Peláez, Jorge

; Fernández Bayón, Gustavo

; Quevedo Pérez, José Ramón

; Coz Velasco, Juan José del

; Luaces Rodríguez, Óscar

; Alonso González, Jaime

; Bahamonde Rionda, Antonio

(2004)

Disease liability prediction from large scale genotyping data using classifiers with a reject option

Quevedo Pérez, José Ramón

; Bahamonde Rionda, Antonio

; Pérez Enciso, Miguel; Luaces Rodríguez, Óscar

(IEEE, 2012)

Dynamic ensemble selection for quantification tasks

Pérez Gallego, Pablo José

; Castaño Gutiérrez, Alberto

; Quevedo Pérez, José Ramón

; Coz Velasco, Juan José del

(Elsevier, 2018)

Ensembles of Quantifiers

Pérez Gallego, Pablo José

(2017-07-21)

Explaining the genetic basis of complex quantitative traits through prediction models

Luaces Rodríguez, Óscar

; Quevedo Pérez, José Ramón

; Pérez Enciso, Miguel; Díez Peláez, Jorge

; Coz Velasco, Juan José del

; Bahamonde Rionda, Antonio

(Mary Ann Liebert, 2010)

A family of admissible heuristics for A* to perform inference in probabilistic classifier chains

Mena Waldo, Deiner

; Montañés Roces, Elena

; Quevedo Pérez, José Ramón

; Coz Velasco, Juan José del

(Springer, 2017)

Feature selection for classification of animal feed ingredients from near infrared microscopy spectra

Sánchez del Rivero, José Antonio

; Montañés Roces, Elena

; Roza Delgado, María Begoña de la; Soldado Cabezuelo, Ana Belén

; Luaces Rodríguez, Óscar

; Quevedo Pérez, José Ramón

; Bahamonde Rionda, Antonio

(Elsevier, 2013)

Browsing by author "Quevedo Pérez, José Ramón"

Adapting Decision DAGs for Multipartite Ranking ﻿

Aggregating independent and dependent models to learn multi-label classifiers ﻿

Ajuste de ponderaciones de una rúbrica a partir de juicios de preferencias del docente ﻿

Analyzing sensory data using non-linear preference learning with feature subset selection ﻿

Analyzing superstars’ power using support vector machines ﻿

Artificial intelligence techniques point out differences in classification performance between light and standard bovine carcasses ﻿

Ascertainment of evolutionary processes from the genetic variation associated to each geographic point in a map ﻿

Capturing waste collection planning expert knowledge in a fitness function through preference learning ﻿

Code and Data of the article Improving importance estimation in covariate shift for providing accurate prediction error ﻿

Code and Data of the article Target inductive methods for zero-shot regression ﻿

Collaborative tag recommendation system based on logistic regression ﻿

Dependent binary relevance models for multi-label classification ﻿

Direct side information learning for zero-shot regression ﻿

Discovering relevancies in very difficult regression problems: applications to sensory data analysis ﻿

Disease liability prediction from large scale genotyping data using classifiers with a reject option ﻿

Dynamic ensemble selection for quantification tasks ﻿

Ensembles of Quantifiers ﻿

Explaining the genetic basis of complex quantitative traits through prediction models ﻿

A family of admissible heuristics for A* to perform inference in probabilistic classifier chains ﻿

Feature selection for classification of animal feed ingredients from near infrared microscopy spectra ﻿

Adapting Decision DAGs for Multipartite Ranking

Aggregating independent and dependent models to learn multi-label classifiers

Ajuste de ponderaciones de una rúbrica a partir de juicios de preferencias del docente

Analyzing sensory data using non-linear preference learning with feature subset selection

Analyzing superstars’ power using support vector machines

Artificial intelligence techniques point out differences in classification performance between light and standard bovine carcasses

Ascertainment of evolutionary processes from the genetic variation associated to each geographic point in a map

Capturing waste collection planning expert knowledge in a fitness function through preference learning

Code and Data of the article Improving importance estimation in covariate shift for providing accurate prediction error

Code and Data of the article Target inductive methods for zero-shot regression

Collaborative tag recommendation system based on logistic regression

Dependent binary relevance models for multi-label classification

Direct side information learning for zero-shot regression

Discovering relevancies in very difficult regression problems: applications to sensory data analysis

Disease liability prediction from large scale genotyping data using classifiers with a reject option

Dynamic ensemble selection for quantification tasks

Ensembles of Quantifiers

Explaining the genetic basis of complex quantitative traits through prediction models

A family of admissible heuristics for A* to perform inference in probabilistic classifier chains

Feature selection for classification of animal feed ingredients from near infrared microscopy spectra