 | 2009 |
| 20 |  | Jorge Díez,
Juan José del Coz,
Antonio Bahamonde,
Oscar Luaces:
Soft Margin Trees.
ECML/PKDD (1) 2009: 302-314 |
| 19 |  | Antonio Bahamonde,
Jaime Alonso,
Juan José del Coz,
Jorge Díez,
José Ramón Quevedo,
Oscar Luaces:
Prediction and Inheritance of Phenotypes.
IWINAC (1) 2009: 275-284 |
| 18 |  | Oscar Luaces,
Francisco Taboada,
Guillermo M. Albaiceta,
Luis A. Domínguez,
Pedro Enríquez,
Antonio Bahamonde:
Predicting the probability of survival in intensive care unit patients from a small number of variables and training examples.
Artificial Intelligence in Medicine 45(1): 63-76 (2009) |
| 2008 |
| 17 |  | Jaime Alonso,
Juan José del Coz,
Jorge Díez,
Oscar Luaces,
Antonio Bahamonde:
Learning to Predict One or More Ranks in Ordinal Regression Tasks.
ECML/PKDD (1) 2008: 39-54 |
| 16 |  | Jorge Díez,
Juan José del Coz,
Oscar Luaces,
Antonio Bahamonde:
Clustering people according to their preference criteria.
Expert Syst. Appl. 34(2): 1274-1284 (2008) |
| 2007 |
| 15 |  | Oscar Luaces,
José Ramón Quevedo,
Francisco Taboada,
Guillermo M. Albaiceta,
Antonio Bahamonde:
Prediction of Probability of Survival in Critically Ill Patients Optimizing the Area under the ROC Curve.
IJCAI 2007: 956-961 |
| 14 |  | José Ramón Quevedo,
Antonio Bahamonde,
Oscar Luaces:
A simple and efficient method for variable ranking according to their usefulness for learning.
Computational Statistics & Data Analysis 52(1): 578-595 (2007) |
| 2004 |
| 13 |  | Jorge Díez,
Gustavo F. Bayón,
José Ramón Quevedo,
Juan José del Coz,
Oscar Luaces,
Jaime Alonso,
Antonio Bahamonde:
Discovering Relevancies in Very Difficult Regression Problems: Applications to Sensory Data Analysis.
ECAI 2004: 993-994 |
| 12 |  | Oscar Luaces,
Gustavo F. Bayón,
José Ramón Quevedo,
Jorge Díez,
Juan José del Coz,
Antonio Bahamonde:
Analyzing Sensory Data Using Non-linear Preference Learning with Feature Subset Selection.
ECML 2004: 286-297 |
| 11 |  | Antonio Bahamonde,
Gustavo F. Bayón,
Jorge Díez,
José Ramón Quevedo,
Oscar Luaces,
Juan José del Coz,
Jaime Alonso,
Félix Goyache:
Feature subset selection for learning preferences: a case study.
ICML 2004 |
| 10 |  | Juan José del Coz,
Gustavo F. Bayón,
Jorge Díez,
Oscar Luaces,
Antonio Bahamonde,
Carlos Sañudo:
Trait Selection for Assessing Beef Meat Quality Using Non-linear SVM.
NIPS 2004 |
| 2003 |
| 9 |  | José Ranilla,
Oscar Luaces,
Antonio Bahamonde:
A heuristic for learning decision trees and pruning them into classification rules.
AI Commun. 16(2): 71-87 (2003) |
| 8 |  | Oscar Luaces,
Antonio Bahamonde:
Inflating examples to obtain rules.
Int. J. Intell. Syst. 18(11): 1113-1143 (2003) |
| 2002 |
| 7 |  | Jorge Díez,
Juan José del Coz,
Oscar Luaces,
Félix Goyache,
Jaime Alonso,
A. M. Peña,
Antonio Bahamonde:
Learning to Assess from Pair-Wise Comparisons.
IBERAMIA 2002: 481-490 |
| 6 |  | Jorge Díez Peláez,
José Ranilla,
Oscar Luaces:
Aplicacion de un proceso de seleccion de reglas a un sistema de aprendizaje.
Inteligencia Artificial, Revista Iberoamericana de Inteligencia Artificial 15: (2002) |
| 2000 |
| 5 |  | F. López,
Félix Goyache,
José Ramón Quevedo,
Jaime Alonso,
José Ranilla,
Oscar Luaces,
Antonio Bahamonde,
Juan José del Coz:
Un sistema inteligente para calificar morfológicamente a bovinos de la raza Asturiana de los Valles.
Inteligencia Artificial, Revista Iberoamericana de Inteligencia Artificial 10: 5-17 (2000) |
| 4 |  | Oscar Luaces,
Antonio Bahamonde:
Aprendizaje de la Similitud entre Casos con Valores Discretos y Numericos (Premio Accésit Jose Cuena).
Inteligencia Artificial, Revista Iberoamericana de Inteligencia Artificial 9: 38-44 (2000) |
| 1999 |
| 3 |  | Oscar Luaces,
Juan José del Coz,
José Ramón Quevedo,
Jaime Alonso,
José Ranilla,
Antonio Bahamonde:
Autonomous Clustering for Machine Learning.
IWANN (1) 1999: 497-506 |
| 2 |  | Juan José del Coz,
Oscar Luaces,
José Ramón Quevedo,
Jaime Alonso,
José Ranilla,
Antonio Bahamonde:
Self-Organizing Cases to Find Paradigms.
IWANN (1) 1999: 527-536 |
| 1998 |
| 1 |  | Oscar Luaces,
Jaime Alonso,
Enrique A. de la Cal,
José Ranilla,
Antonio Bahamonde:
Machine Learning Usefulness Relies on Accuracy and Self-Maintenance.
IEA/AIE (Vol. 2) 1998: 448-457 |