J. J. Coz

发表

Learning Nondeterministic Classifiers

Juan José del Coz, Jorge Díez, Antonio Bahamonde, 2009, J. Mach. Learn. Res..

Clustering of preference criteria

J. J. Coz, J. Díez, A. Bahamonde, 2003 .

On the prediction of Hodgkin lymphoma treatment response

J. L. Fernández-Martínez, J. J. Coz, E. J. deAndrés-Galiana, 2015, Clinical and Translational Oncology.

Report on the 1st International Workshop on Learning to Quantify (LQ 2021)

F. Sebastiani, J. J. Coz, Pablo González, 2022, SIGKDD Explor..

Optimizing different loss functions in multilabel classifications

J. J. Coz, J. Díez, A. Bahamonde, 2015, Progress in Artificial Intelligence.

Soft Margin Trees

Juan José del Coz, Oscar Luaces, Jorge Díez, 2009, ECML/PKDD.

Using ensembles for problems with characterizable changes in data distribution: A case study on quantification

José Ramón Quevedo, Juan José del Coz, J. R. Quevedo, 2017, Inf. Fusion.

Clustering people according to their preference criteria

Juan José del Coz, Oscar Luaces, Jorge Díez, 2008, Expert Syst. Appl..

Predicting fertility from seminal traits: Performance of several parametric and non-parametric procedures

Elena Montañés, José Ramón Quevedo, Jorge Díez, 2013 .

The usefulness of artificial intelligence techniques to assess subjective quality of products in the food industry

José Ranilla, José Ramón Quevedo, Oscar Luaces, 2001 .

Using artificial intelligence to design and implement a morphological assessment system in beef cattle

José Ranilla, José Ramón Quevedo, Oscar Luaces, 2001 .

Feature subset selection for learning preferences: a case study

José Ramón Quevedo, Juan José del Coz, Oscar Luaces, 2004, ICML.

Enhancing directed binary trees for multi-class classification

Elena Montañés, Juan José del Coz, José Barranquero, 2013, Inf. Sci..

Analysis of clinical prognostic variables for Chronic Lymphocytic Leukemia decision-making problems

Enrique J. deAndrés-Galiana, Oscar Luaces, Juan Luis Fernández Martínez, 2016, J. Biomed. Informatics.

Proceedings of the 2nd International Workshop on Learning to Quantify (LQ 2022)

F. Sebastiani, J. J. Coz, Pablo González, 2022 .

Learning to Quantify: Methods and Applications (LQ 2021)

Fabrizio Sebastiani, Juan José del Coz, Alejandro Moreo, 2021, CIKM.

A Review on Quantification Learning

Nitesh V. Chawla, Juan José del Coz, Pablo González, 2017, ACM Comput. Surv..

Quantification-oriented learning based on reliable classifiers

Juan José del Coz, Jorge Díez, José Barranquero, 2015, Pattern Recognit..

Dynamic ensemble selection for quantification tasks

José Ramón Quevedo, Juan José del Coz, J. R. Quevedo, 2019, Inf. Fusion.

On the study of nearest neighbor algorithms for prevalence estimation in binary problems

Juan José del Coz, Jorge Díez, Pablo González, 2013, Pattern Recognit..

Adapting Decision DAGs for Multipartite Ranking

Elena Montañés, José Ramón Quevedo, Juan José del Coz, 2010, ECML/PKDD.

Binary relevance efficacy for multilabel classification

Juan José del Coz, Oscar Luaces, Antonio Bahamonde, 2012, Progress in Artificial Intelligence.

Deep learning to frame objects for visual target tracking

Zhezhou Yu, Shu-Chao Pang, Juan José del Coz, 2017, Eng. Appl. Artif. Intell..

Improving the ε-approximate algorithm for Probabilistic Classifier Chains

José Ramón Quevedo, Juan José del Coz, J. R. Quevedo, 2020, Knowl. Inf. Syst..

Rectifying Classifier Chains for Multi-Label Classification pdf

Eyke Hüllermeier, Robin Senge, Juan José del Coz, 2019, LWA.

An overview of inference methods in probabilistic classifier chains for multilabel classification

Elena Montañés, José Ramón Quevedo, Juan José del Coz, 2016, WIREs Data Mining Knowl. Discov..

Dependent binary relevance models for multi-label classification

Eyke Hüllermeier, Elena Montañés, José Ramón Quevedo, 2014, Pattern Recognit..

Aggregating Independent and Dependent Models to Learn Multi-label Classifiers

Elena Montañés, José Ramón Quevedo, Juan José del Coz, 2011, ECML/PKDD.

A semi-dependent decomposition approach to learn hierarchical classifiers

Juan José del Coz, Jorge Díez, Antonio Bahamonde, 2010, Pattern Recognit..

Using A* for Inference in Probabilistic Classifier Chains

Elena Montañés, José Ramón Quevedo, Juan José del Coz, 2015, IJCAI.