Juan José del Coz
Juan José del Coz
Artificial Intelligent Center - University of Oviedo
Verified email at uniovi.es - Homepage
TitleCited byYear
Binary relevance efficacy for multilabel classification
O Luaces, J Díez, J Barranquero, JJ del Coz, A Bahamonde
Progress in Artificial Intelligence 1 (4), 303-313, 2012
Dependent binary relevance models for multi-label classification
E Montañes, R Senge, J Barranquero, JR Quevedo, JJ del Coz, ...
Pattern Recognition 47 (3), 1494-1508, 2014
Feature subset selection for learning preferences: A case study
A Bahamonde, GF Bayón, J Díez, JR Quevedo, O Luaces, JJ Del Coz, ...
Proceedings of the twenty-first international conference on Machine learning, 7, 2004
Development of a distributive control scheme for fluorescent lighting based on LonWorks technology
JM Alonso, J Ribas, JJD Coz, AJ Calleja, EL Corominas, M Rico-Secades
IEEE Transactions on Industrial Electronics 47 (6), 1253-1262, 2000
Learning nondeterministic classifiers
JJ Coz, J Díez, A Bahamonde
Journal of Machine Learning Research 10 (Oct), 2273-2293, 2009
The usefulness of artificial intelligence techniques to assess subjective quality of products in the food industry
F Goyache, A Bahamonde, J Alonso, S López, JJ Del Coz, JR Quevedo, ...
Trends in Food Science & Technology 12 (10), 370-381, 2001
Quantification-oriented learning based on reliable classifiers
J Barranquero, J Díez, JJ del Coz
Pattern Recognition 48 (2), 591-604, 2015
On the problem of error propagation in classifier chains for multi-label classification
R Senge, JJ Del Coz, E Hüllermeier
Data Analysis, Machine Learning and Knowledge Discovery, 163-170, 2014
Artificial intelligence techniques point out differences in classification performance between light and standard bovine carcasses
J Dıez, A Bahamonde, J Alonso, S López, JJ Del Coz, JR Quevedo, ...
Meat Science 64 (3), 249-258, 2003
On the study of nearest neighbor algorithms for prevalence estimation in binary problems
J Barranquero, P González, J Díez, JJ Del Coz
Pattern Recognition 46 (2), 472-482, 2013
Clustering people according to their preference criteria
J Díez, JJ Del Coz, O Luaces, A Bahamonde
Expert Systems with Applications 34 (2), 1274-1284, 2008
How to learn consumer preferences from the analysis of sensory data by means of support vector machines (SVM)
A Bahamonde, J Díez, JR Quevedo, O Luaces, JJ del Coz
Trends in food science & technology 18 (1), 20-28, 2007
Trait selection for assessing beef meat quality using non-linear SVM
J Coz, GF Bayón, J Díez, O Luaces, A Bahamonde, C Sañudo
Advances in Neural Information Processing Systems, 321-328, 2005
Aggregating independent and dependent models to learn multi-label classifiers
E Montañés, JR Quevedo, JJ del Coz
Joint European Conference on Machine Learning and Knowledge Discovery in …, 2011
Analyzing sensory data using non-linear preference learning with feature subset selection
O Luaces, GF Bayón, JR Quevedo, J Díez, JJ Del Coz, A Bahamonde
European Conference on Machine Learning, 286-297, 2004
Using ensembles for problems with characterizable changes in data distribution: A case study on quantification
P Pérez-Gállego, JR Quevedo, JJ del Coz
Information Fusion 34, 87-100, 2017
Rectifying classifier chains for multi-label classification
R Senge, JJ del Coz, E Hüllermeier
arXiv preprint arXiv:1906.02915, 2019
Identifying market segments in beef: Breed, slaughter weight and ageing time implications
J Díez, JJ Del Coz, A Bahamonde, C Sañudo, JL Olleta, S Macie, ...
Meat science 74 (4), 667-675, 2006
Discovering relevancies in very difficult regression problems: applications to sensory data analysis
J Díez Peláez, G Fernández Bayón, JR Quevedo Pérez, JJ Coz Velasco, ...
Proceedings of the European conference on artificial intelligence (ECAI’04), 2004
Using artificial intelligence to design and implement a morphological assessment system in beef cattle
F Goyache, JJ Del Coz, JR Quevedo, S López, J Alonso, J Ranilla, ...
Animal Science 73 (1), 49-60, 2001
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