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2018

Reyes, O; Cano, A; Fardoun, H; Ventura, S

A locally weighted learning method based on a data gravitation model for multi-target regression Journal Article

International Journal of Computational Intelligence Systems, 11 (1), pp. 282-295, 2018.

BibTeX | Tags: Multi-label Learning, Supervised Learning

Moyano, J M; Gibaja, E; Cios, K J; Ventura, S

Review of ensembles of multi-label classifiers: Models, experimental study and prospects Journal Article

Information Fusion, 44 , pp. 33 - 45, 2018, ISSN: 1566-2535.

Links | BibTeX | Tags: Classification, Multi-label Learning, Supervised Learning

Moyano, J M; Gibaja, E; Cios, K J; Ventura, S

An evolutionary approach to build ensembles of multi-label classifiers Journal Article

Information Fusion, 2018, ISSN: 1566-2535.

Links | BibTeX | Tags: Classification, Evolutionary Algorithms, Multi-label Learning, Supervised Learning

2017

Moyano, J M; Gibaja, E; Ventura, S

An evolutionary algorithm for optimizing the target ordering in Ensemble of Regressor Chains Inproceedings

2017 IEEE Congress on Evolutionary Computation (CEC), pp. 2015-2021, 2017.

Links | BibTeX | Tags: Evolutionary Algorithms, Multi-label Learning, Supervised Learning

Maestre-García, F J; García-Martínez, C; Pérez-Ortíz, M; Gutiérrez, P A

An Iterated Greedy Algorithm for Improving the Generation of Synthetic Patterns in Imbalanced Learning Inproceedings

Proceedings of the International Work-Conference on Artificial Neural Networks: Advances in Computational Intelligence, pp. 513-524, Cadiz, Spain, 2017.

BibTeX | Tags: Classification, Metaheuristics, Supervised Learning

Melki, G; Cano, A; Kecman, V; Ventura, S

Multi-Target Support Vector Regression Via Correlation Regressor Chains Journal Article

Information Sciences, 415-416 , pp. 53-69, 2017.

Links | BibTeX | Tags: Multi-label Learning, Supervised Learning

Krawczyk, B; McInnes, B; Cano, A

Sentiment Classification from Multi-class Imbalanced Twitter Data Using Binarization Inproceedings

Proceedings of the 12th International Conference on Hybrid Artificial Intelligent Systems, pp. 26-37, 2017.

BibTeX | Tags: Classification, Supervised Learning

2016

Cano, A; Nguyen, D T; Ventura, S; Cios, K J

ur-CAIM: improved CAIM discretization for unbalanced and balanced data Journal Article

Soft Computing, 20 (1), pp. 173-188, 2016.

Links | BibTeX | Tags: Classification, Supervised Learning

Fuentes-Alventosa, J; Romero, C; García-Martínez, C; Ventura, S

Predicción de la aceptación o rechazo de las calificaciones finales propuestas por el alumnado usando técnicas de Minería de Datos Inproceedings

Actas de las XXII Jornadas sobre la Enseñanza Universitaria de la Informática (JENUI 2016), pp. 201–208, 2016, ISBN: 9788416642304.

Links | BibTeX | Tags: Classification, Educational Data Mining, Predicting Student Performance, Supervised Learning

Reyes, O; Morell, C; Ventura, S

Effective lazy learning algorithm based on a data gravitation model for multi-label learning Journal Article

Information Sciences, 340 (341), pp. 159-174, 2016.

Links | BibTeX | Tags: Multi-label Learning, Supervised Learning

2015

Moyano, J M; Gibaja, E; Cano, A; Luna, J M; Ventura, S

Diseño automático de multi-clasificadores basados en proyecciones de etiquetas Inproceedings

XVI Conferencia de la Asociación Española para la Inteligencia Artificial, pp. 355–365, 2015.

Links | BibTeX | Tags: Classification, Evolutionary Algorithms, Multi-label Learning, Supervised Learning

Moyano, J M; Gibaja, E; Cano, A; Luna, J M; Ventura, S

Algoritmo evolutivo para optimizar ensembles de clasificadores multi-etiqueta Inproceedings

X Congreso Español sobre Metaheurísticas and Algoritmos Evolutivos y Bioinspirados, pp. 219-225, 2015.

Links | BibTeX | Tags: Classification, Evolutionary Algorithms, Multi-label Learning, Supervised Learning

Reyes, O; Morell, C; Ventura, S

Scalable extensions of the ReliefF algorithm for weighting and selecting features on the multi-label learning context Journal Article

Neurocomputing, 161 , pp. 168–182, 2015.

Links | BibTeX | Tags: Data Preprocessing, Feature Selection, Multi-label Learning, Supervised Learning

2014

Fuentes-Alventosa, J; Romero, C; García-Martínez, C; Ventura, S

Accepting or Rejecting Students' Self-grading in Their Final Marks by using Data Mining Inproceedings

International Conference on Educational Data Mining (EDM'14), pp. 327–328, 2014.

Links | BibTeX | Tags: Classification, Educational Data Mining, Predicting Student Performance, Supervised Learning

Pedraza, J A; García-Martínez, C; Cano, A; Ventura, S

Classification Rule Mining with Iterated Greedy Inproceedings

International Conference on Hybrid Artificial Intelligence Systems, pp. 585–596, 2014.

Links | BibTeX | Tags: Classification, Supervised Learning

Reyes, O; Morell, C; Ventura, S

Evolutionary feature weighting to improve the performance of multi-label lazy algorithms Journal Article

Integrated Computer-Aided Engineering, 21 (4), pp. 339-354, 2014.

Links | BibTeX | Tags: Data Preprocessing, Evolutionary Algorithms, Multi-label Learning, Supervised Learning

2013

Reyes, O; Morell, C; Ventura, S

ReliefF-ML: An Extension of ReliefF Algorithm to Multi-label Learning Inproceedings

Ruiz-Shulcloper, J; Sanniti di Baja, G (Ed.): Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications: 18th Iberoamerican Congress (CIARP-2013), Havana, Cuba, November 20-23, 2013, Proceedings, Part II, pp. 528-535, Springer Berlin Heidelberg, 2013.

Links | BibTeX | Tags: Data Preprocessing, Multi-label Learning, Supervised Learning

Reyes, O; Morell, C; Ventura, S

Feature weighting on multi-label data through quadratic loss minimization Inproceedings

Congreso Internacional de Matemática y Computación (COMPUMAT-2013), 2013.

Links | BibTeX | Tags: Data Preprocessing, Evolutionary Algorithms, Multi-label Learning, Supervised Learning

2012

Reyes, O; Morell, C; Ventura, S

Learning similarity metric to improve the performance of lazy multi-label ranking algorithms Inproceedings

Proceedings of the 12th International Conference on Intelligent Systems Design and Applications, ISDA'12, pp. 246-251, 2012.

Links | BibTeX | Tags: Data Preprocessing, Evolutionary Algorithms, Multi-label Learning, Supervised Learning

2010

Olmo, J L; Luna, J M; Romero, J R; Ventura, S

Minería de Reglas de Clasificación mediante un Algoritmo de Programación Automática con Hormigas Inproceedings

VII Congreso Español sobre Metaheurísticas and Algoritmos Evolutivos y Bioinspirados, pp. 243-250, Valencia, España, 2010.

BibTeX | Tags: Ant Programming, Bioinspired algorithms, Classification, Evolutionary Algorithms, Supervised Learning

Olmo, J L; Luna, J M; Romero, J R; Ventura, S

An Automatic Programming ACO-Based Algorithm for Classification Rule Mining Inproceedings

Proceedings of the 8th International Conference on Practical Applications of Agents and Multiagent Systems, pp. 649–656, Salamanca, Spain, 2010.

Links | BibTeX | Tags: Ant Programming, Bioinspired algorithms, Classification, Evolutionary Algorithms, Supervised Learning

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