2022
|
Moyano, J M; Ventura, S Auto-adaptive Grammar-Guided Genetic Programming algorithm to build Ensembles of Multi-Label Classifiers Journal Article Information Fusion, 78 , pp. 1-19, 2022, ISSN: 1566-2535. Links | BibTeX | Tags: Classification, Evolutionary Algorithms, Genetic Programming, Multi-label Learning, Supervised Learning @article{Moyano:2022a_INFFUS,
title = {Auto-adaptive Grammar-Guided Genetic Programming algorithm to build Ensembles of Multi-Label Classifiers},
author = {Moyano, J. M. and Ventura, S.},
url = {http://www.sciencedirect.com/science/article/pii/S1566253521001469},
doi = {10.1016/j.inffus.2021.07.005},
issn = {1566-2535},
year = {2022},
date = {2022-01-01},
journal = {Information Fusion},
volume = {78},
pages = {1-19},
keywords = {Classification, Evolutionary Algorithms, Genetic Programming, Multi-label Learning, Supervised Learning},
pubstate = {published},
tppubtype = {article}
}
|
Esteban, A; Zafra, A; Ventura, S Data mining in predictive maintenance systems: A taxonomy and systematic review Journal Article Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, pp. e1471, 2022. Links | BibTeX | Tags: Anomaly Detection, Data Science, Feature Selection, Predictive Maintenance, Supervised Learning, Unsupervised Learning @article{esteban2022data,
title = {Data mining in predictive maintenance systems: A taxonomy and systematic review},
author = {Esteban, A. and Zafra, A. and Ventura, S.},
url = {https://wires.onlinelibrary.wiley.com/doi/10.1002/widm.1471},
doi = {10.1002/widm.1471},
year = {2022},
date = {2022-01-01},
journal = {Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery},
pages = {e1471},
publisher = {Wiley Online Library},
keywords = {Anomaly Detection, Data Science, Feature Selection, Predictive Maintenance, Supervised Learning, Unsupervised Learning},
pubstate = {published},
tppubtype = {article}
}
|
López-Zambrano, J; Lara, J; Romero, C Improving the portability of predicting students’ performance models by using ontologies Journal Article Journal of Computing in Higher Education, 34 (1), pp. 1-19, 2022. Links | BibTeX | Tags: Data Science, Educational Data Mining, Supervised Learning @article{LopezZambrano2022,
title = {Improving the portability of predicting students’ performance models by using ontologies},
author = {L\'{o}pez-Zambrano, J. and Lara, J. and Romero, C.},
url = {https://link.springer.com/article/10.1007/s12528-021-09273-3},
year = {2022},
date = {2022-01-01},
journal = {Journal of Computing in Higher Education},
volume = {34},
number = {1},
pages = {1-19},
publisher = {Springer US},
keywords = {Data Science, Educational Data Mining, Supervised Learning},
pubstate = {published},
tppubtype = {article}
}
|
Maqsood, R; Ceravolo, P; Romero, C; Ventura, S Modeling and predicting students’ engagement behaviors using mixture Markov models Journal Article Knowledge and Information Systems, pp. 1-36, 2022. Links | BibTeX | Tags: Data Science, Educational Data Mining, Educational Recommender Systems, Supervised Learning @article{Maqsood2022,
title = {Modeling and predicting students’ engagement behaviors using mixture Markov models},
author = {Maqsood, R. and Ceravolo, P. and Romero, C. and Ventura, S.},
url = {https://link.springer.com/article/10.1007/s10115-022-01674-9},
year = {2022},
date = {2022-01-01},
journal = {Knowledge and Information Systems},
pages = {1-36},
publisher = {Springer London},
keywords = {Data Science, Educational Data Mining, Educational Recommender Systems, Supervised Learning},
pubstate = {published},
tppubtype = {article}
}
|
Belmonte, A; Zafra, A; Gibaja, E MIML library: a Modular and Flexible Library for Multi-instance Multi-label Learning Journal Article Neurocomputing, 2022. Links | BibTeX | Tags: Data Science, Library, Multi-instance Learning, Multi-label Learning, Software, Supervised Learning @article{belmonte2022miml,
title = {MIML library: a Modular and Flexible Library for Multi-instance Multi-label Learning},
author = {Belmonte, A. and Zafra, A. and Gibaja, E.},
url = {https://www.sciencedirect.com/science/article/pii/S0925231222006518},
doi = {10.1016/j.neucom.2022.05.068},
year = {2022},
date = {2022-01-01},
journal = {Neurocomputing},
publisher = {Elsevier},
keywords = {Data Science, Library, Multi-instance Learning, Multi-label Learning, Software, Supervised Learning},
pubstate = {published},
tppubtype = {article}
}
|
Ramírez, A; Romero, J M Synergies between artificial intelligence and software engineering: evolution and trends Incollection Virvou, M; Tsihrintzis, G A; Bourbakis, N G; Jain, L C (Ed.): Handbook on Artificial Intelligence-Empowered Applied Software Engineering, 1 , Springer, 2022. BibTeX | Tags: Deep Learning, Search-based Software Engineering, Software analytics, Supervised Learning, Unsupervised Learning @incollection{ramirez2022chapter1,
title = {Synergies between artificial intelligence and software engineering: evolution and trends},
author = {Ram\^{i}rez, A. and Romero, J. M.},
editor = {Virvou, M. and Tsihrintzis, G. A. and Bourbakis, N. G. and Jain, L. C.},
year = {2022},
date = {2022-01-01},
booktitle = {Handbook on Artificial Intelligence-Empowered Applied Software Engineering},
volume = {1},
publisher = {Springer},
keywords = {Deep Learning, Search-based Software Engineering, Software analytics, Supervised Learning, Unsupervised Learning},
pubstate = {published},
tppubtype = {incollection}
}
|
Ramírez, A; Miranda, B Foundations of Machine Learning for Software Engineering Incollection Romero, J R; Chicano, F; Medina-Bulo, I (Ed.): Optimising the software development process with artificial intelligence, Springer, 2022. BibTeX | Tags: Classification, Clustering, Data Preprocessing, Deep Learning, Software analytics, Supervised Learning, Unsupervised Learning @incollection{ramirez2022chapter2,
title = {Foundations of Machine Learning for Software Engineering},
author = {Ram\^{i}rez, A. and Miranda, B.},
editor = {Romero, J. R. and Chicano, F. and Medina-Bulo, I.},
year = {2022},
date = {2022-01-01},
booktitle = {Optimising the software development process with artificial intelligence},
publisher = {Springer},
keywords = {Classification, Clustering, Data Preprocessing, Deep Learning, Software analytics, Supervised Learning, Unsupervised Learning},
pubstate = {published},
tppubtype = {incollection}
}
|
Moyano, J M; Luna, J M; Ventura, S Reducing the label space a predefined ratio for a more efficient multi-label classification Journal Article IEEE Access, 10 , pp. 76480-76492, 2022, ISSN: 2169-3536. Links | BibTeX | Tags: Classification, Data Science, Multi-label Learning, Supervised Learning @article{Moyano:2022b_IEEEAccess,
title = {Reducing the label space a predefined ratio for a more efficient multi-label classification},
author = {Moyano, J. M. and Luna, J. M. and Ventura, S.},
url = {https://ieeexplore.ieee.org/document/9833489},
doi = {10.1109/ACCESS.2022.3192642},
issn = {2169-3536},
year = {2022},
date = {2022-01-01},
journal = {IEEE Access},
volume = {10},
pages = {76480-76492},
keywords = {Classification, Data Science, Multi-label Learning, Supervised Learning},
pubstate = {published},
tppubtype = {article}
}
|
2021
|
Frias, M; Moyano, J M; Rivero-Juarez, A; Luna, J M; Camacho, A; Fardoun, H M; Machuca, I; Al-Twijri, M; Rivero, A; Ventura, S Classification Accuracy of Hepatitis C Virus Infection Outcome: Data Mining Approach Journal Article Journal of Medical Internet Research, 23 (2), pp. e18766, 2021, ISSN: 1438-8871. Links | BibTeX | Tags: Classification, Clinical Data Mining, Feature Selection, Supervised Learning @article{Moyano:2021b_JMIR,
title = {Classification Accuracy of Hepatitis C Virus Infection Outcome: Data Mining Approach},
author = {Frias, M. and Moyano, J. M. and Rivero-Juarez, A. and Luna, J. M. and Camacho, A. and Fardoun, H. M. and Machuca, I. and Al-Twijri, M. and Rivero, A. and Ventura, S.},
url = {https://doi.org/10.2196/18766},
doi = {10.2196/18766},
issn = {1438-8871},
year = {2021},
date = {2021-01-01},
journal = {Journal of Medical Internet Research},
volume = {23},
number = {2},
pages = {e18766},
keywords = {Classification, Clinical Data Mining, Feature Selection, Supervised Learning},
pubstate = {published},
tppubtype = {article}
}
|
Moyano, J M; Reyes, O; Fardoun, H M; Ventura, S Performing multi-target regression via gene expression programming-based ensemble models Journal Article Neurocomputing, 432 , pp. 275-287, 2021, ISSN: 1872-8286. Links | BibTeX | Tags: Evolutionary Algorithms, Gene Expression Programming (GEP), Multi-target Regression, Supervised Learning @article{Moyano:2021a_Neurocomputing,
title = {Performing multi-target regression via gene expression programming-based ensemble models},
author = {Moyano, J. M. and Reyes, O. and Fardoun, H. M. and Ventura, S.},
url = {https://www.sciencedirect.com/science/article/abs/pii/S0925231220319603},
doi = {10.1016/j.neucom.2020.12.060},
issn = {1872-8286},
year = {2021},
date = {2021-01-01},
journal = {Neurocomputing},
volume = {432},
pages = {275-287},
keywords = {Evolutionary Algorithms, Gene Expression Programming (GEP), Multi-target Regression, Supervised Learning},
pubstate = {published},
tppubtype = {article}
}
|
Cachi, P; Ventura, S; Cios, K J CRBA: A Competitive Rate-Based Algorithm Based on Competitive Spiking Neural Networks Journal Article Frontiers in computational neuroscience, 15 , pp. 627567, 2021. Links | BibTeX | Tags: Classification, Data Science, Supervised Learning @article{cachi2021crba,
title = {CRBA: A Competitive Rate-Based Algorithm Based on Competitive Spiking Neural Networks},
author = {Cachi, P. and Ventura, S. and Cios, K. J.},
url = {https://www.frontiersin.org/articles/10.3389/fncom.2021.627567/full},
doi = {10.3389/fncom.2021.627567},
year = {2021},
date = {2021-01-01},
journal = {Frontiers in computational neuroscience},
volume = {15},
pages = {627567},
publisher = {Frontiers Media SA url=https://www.frontiersin.org/articles/10.3389/fncom.2021.627567},
keywords = {Classification, Data Science, Supervised Learning},
pubstate = {published},
tppubtype = {article}
}
|
Chango, W; Cerezo, R; Sanchez-Santillan, M; Azevedo, R; Romero, C Improving prediction of students’ performance in intelligent tutoring systems using attribute selection and ensembles of different multimodal data sources Journal Article Journal of Computing in Higher Education, 33 (3), pp. 614–634, 2021. Links | BibTeX | Tags: Classification, Data Science, Educational Data Mining, Supervised Learning @article{chango2021improving,
title = {Improving prediction of students’ performance in intelligent tutoring systems using attribute selection and ensembles of different multimodal data sources},
author = {Chango, W. and Cerezo, R. and Sanchez-Santillan, M. and Azevedo, R. and Romero, C.},
url = {https://link.springer.com/article/10.1007/s12528-021-09298-8},
year = {2021},
date = {2021-01-01},
journal = {Journal of Computing in Higher Education},
volume = {33},
number = {3},
pages = {614--634},
publisher = {Springer},
keywords = {Classification, Data Science, Educational Data Mining, Supervised Learning},
pubstate = {published},
tppubtype = {article}
}
|
Ramírez, A; Moreno, N; Vallecillo, A Rule-based preprocessing for data stream mining using complex event processing Journal Article Expert Systems, 38 (8), pp. e12762, 2021. Links | BibTeX | Tags: Classification, Data Preprocessing, Supervised Learning @article{ramirez2021rule,
title = {Rule-based preprocessing for data stream mining using complex event processing},
author = {Ram\^{i}rez, A. and Moreno, N. and Vallecillo, A.},
url = {https://onlinelibrary.wiley.com/doi/full/10.1111/exsy.12762},
doi = {10.1111/exsy.12762},
year = {2021},
date = {2021-01-01},
journal = {Expert Systems},
volume = {38},
number = {8},
pages = {e12762},
publisher = {Wiley Online Library},
keywords = {Classification, Data Preprocessing, Supervised Learning},
pubstate = {published},
tppubtype = {article}
}
|
2020
|
Moyano, J M; Gibaja, E; Cios, K J; Ventura, S Combining multi-label classifiers based on projections of the output space using Evolutionary algorithms Journal Article Knowledge-Based Systems, 196 , pp. 105770, 2020, ISSN: 0950-7051. Links | BibTeX | Tags: Classification, Evolutionary Algorithms, Multi-label Learning, Supervised Learning @article{Moyano:2020a_KBS,
title = {Combining multi-label classifiers based on projections of the output space using Evolutionary algorithms},
author = {Moyano, J. M. and Gibaja, E. and Cios, K. J. and Ventura, S.},
url = {https://www.sciencedirect.com/science/article/pii/S0950705120301726},
doi = {10.1016/j.knosys.2020.105770},
issn = {0950-7051},
year = {2020},
date = {2020-01-01},
journal = {Knowledge-Based Systems},
volume = {196},
pages = {105770},
keywords = {Classification, Evolutionary Algorithms, Multi-label Learning, Supervised Learning},
pubstate = {published},
tppubtype = {article}
}
|
Moyano, J M; Gibaja, E; Cios, K J; Ventura, S Tree-shaped ensemble of multi-label classifiers using grammar-guided genetic programming Inproceedings 2020 IEEE Congress on Evolutionary Computation, CEC 2020, pp. 1-8, 2020. Links | BibTeX | Tags: Evolutionary Algorithms, Genetic Programming, Multi-label Learning, Supervised Learning @inproceedings{Moyano:2020c_CEC,
title = {Tree-shaped ensemble of multi-label classifiers using grammar-guided genetic programming},
author = {Moyano, J. M. and Gibaja, E. and Cios, K. J. and Ventura, S.},
url = {https://ieeexplore.ieee.org/abstract/document/9185661},
doi = {10.1109/CEC48606.2020.9185661},
year = {2020},
date = {2020-01-01},
booktitle = {2020 IEEE Congress on Evolutionary Computation, CEC 2020},
pages = {1-8},
keywords = {Evolutionary Algorithms, Genetic Programming, Multi-label Learning, Supervised Learning},
pubstate = {published},
tppubtype = {inproceedings}
}
|
Moyano, J M; Gibaja, E; Cios, K J; Ventura, S Generating ensembles of multi-label classifiers using cooperative coevolutionary algorithms Inproceedings 24th European Conference on Artificial Intelligence, ECAI 2020, pp. 497, 2020. Links | BibTeX | Tags: Evolutionary Algorithms, Multi-label Learning, Supervised Learning @inproceedings{Moyano:2020b_ECAI,
title = {Generating ensembles of multi-label classifiers using cooperative coevolutionary algorithms},
author = {Moyano, J. M. and Gibaja, E. and Cios, K. J. and Ventura, S.},
url = {https://ecai2020.eu/papers/497_paper.pdf},
doi = {10.3233/FAIA200242},
year = {2020},
date = {2020-01-01},
booktitle = {24th European Conference on Artificial Intelligence, ECAI 2020},
pages = {497},
keywords = {Evolutionary Algorithms, Multi-label Learning, Supervised Learning},
pubstate = {published},
tppubtype = {inproceedings}
}
|
Cachi, P; Ventura, S; Cios, K J Fast Convergence of Competitive Spiking Neural Networks with Sample-Based Weight Initialization Inproceedings pp. 773-786, Springer, Cham, 2020. Links | BibTeX | Tags: Classification, Data Science, Supervised Learning @inproceedings{Cachi2020,
title = {Fast Convergence of Competitive Spiking Neural Networks with Sample-Based Weight Initialization},
author = {Cachi, P. and Ventura, S. and Cios, K. J.},
url = {https://link.springer.com/chapter/10.1007/978-3-030-50153-2_57},
year = {2020},
date = {2020-01-01},
pages = {773-786},
publisher = {Springer, Cham},
keywords = {Classification, Data Science, Supervised Learning},
pubstate = {published},
tppubtype = {inproceedings}
}
|
Pinargote-Ortega, M; Bowen-Mendoza, L; Meza, J; Ventura, S Accuracy Measures of Sentiment Analysis Algorithms for Spanish Corpus generated in Peer Assessment Inproceedings pp. 1-7, 2020. Links | BibTeX | Tags: Classification, Data Science, Supervised Learning @inproceedings{Pinargote2020,
title = {Accuracy Measures of Sentiment Analysis Algorithms for Spanish Corpus generated in Peer Assessment},
author = {Pinargote-Ortega, M. and Bowen-Mendoza, L. and Meza, J. and Ventura, S.},
url = {https://dl.acm.org/doi/abs/10.1145/3410352.3410838},
year = {2020},
date = {2020-01-01},
pages = {1-7},
keywords = {Classification, Data Science, Supervised Learning},
pubstate = {published},
tppubtype = {inproceedings}
}
|
2019
|
Moyano, J M; Gibaja, E; Cios, K J; Ventura, S An evolutionary approach to build ensembles of multi-label classifiers Journal Article Information Fusion, 50 , pp. 168-180, 2019, ISSN: 1566-2535. Links | BibTeX | Tags: Classification, Evolutionary Algorithms, Multi-label Learning, Supervised Learning @article{Moyanoa2018b_INFFUS,
title = {An evolutionary approach to build ensembles of multi-label classifiers},
author = {Moyano, J. M. and Gibaja, E. and Cios, K. J. and Ventura, S.},
url = {http://www.sciencedirect.com/science/article/pii/S1566253518302574},
doi = {10.1016/j.inffus.2018.11.013},
issn = {1566-2535},
year = {2019},
date = {2019-01-01},
journal = {Information Fusion},
volume = {50},
pages = {168-180},
keywords = {Classification, Evolutionary Algorithms, Multi-label Learning, Supervised Learning},
pubstate = {published},
tppubtype = {article}
}
|
Moyano, J M; Gibaja, E; Ventura, S; Cano, A Speeding up classifier chains in multi-label classification Inproceedings IoTBDS 2019 - Proceedings of the 4th International Conference on Internet of Things, Big Data and Security, pp. 29-37, 2019. Links | BibTeX | Tags: Classification, Multi-label Learning, Scalability, Supervised Learning @inproceedings{Moyano201929,
title = {Speeding up classifier chains in multi-label classification},
author = {Moyano, J. M. and Gibaja, E. and Ventura, S. and Cano, A.},
url = {http://www.scitepress.org/DigitalLibrary/Link.aspx?doi=10.5220/0007614200290037},
year = {2019},
date = {2019-01-01},
booktitle = {IoTBDS 2019 - Proceedings of the 4th International Conference on Internet of Things, Big Data and Security},
pages = {29-37},
keywords = {Classification, Multi-label Learning, Scalability, Supervised Learning},
pubstate = {published},
tppubtype = {inproceedings}
}
|
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 @article{2017-IJCIS,
title = {A locally weighted learning method based on a data gravitation model for multi-target regression},
author = {Reyes, O. and Cano, A. and Fardoun, H. and Ventura, S.},
year = {2018},
date = {2018-01-01},
journal = {International Journal of Computational Intelligence Systems},
volume = {11},
number = {1},
pages = {282-295},
keywords = {Multi-label Learning, Supervised Learning},
pubstate = {published},
tppubtype = {article}
}
|
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 @article{Moyanoa2018a_INFFUS,
title = {Review of ensembles of multi-label classifiers: Models, experimental study and prospects},
author = {Moyano, J. M. and Gibaja, E. and Cios, K. J. and Ventura, S.},
url = {http://www.sciencedirect.com/science/article/pii/S1566253517307169},
doi = {10.1016/j.inffus.2017.12.001},
issn = {1566-2535},
year = {2018},
date = {2018-01-01},
journal = {Information Fusion},
volume = {44},
pages = {33 - 45},
keywords = {Classification, Multi-label Learning, Supervised Learning},
pubstate = {published},
tppubtype = {article}
}
|
Reyes, O; Morell, C; Ventura, S Effective active learning strategy for multi-label learning Journal Article Neurocomputing, 273 , pp. 494-508, 2018. Links | BibTeX | Tags: Classification, Multi-label Learning, Scalability, Supervised Learning @article{Reyes2018494,
title = {Effective active learning strategy for multi-label learning},
author = {Reyes, O. and Morell, C. and Ventura, S.},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85028403971&doi=10.1016%2fj.neucom.2017.08.001&partnerID=40&md5=05e151b407c022b621123a619712e214},
doi = {10.1016/j.neucom.2017.08.001},
year = {2018},
date = {2018-01-01},
journal = {Neurocomputing},
volume = {273},
pages = {494-508},
keywords = {Classification, Multi-label Learning, Scalability, Supervised Learning},
pubstate = {published},
tppubtype = {article}
}
|
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 @inproceedings{7969548,
title = {An evolutionary algorithm for optimizing the target ordering in Ensemble of Regressor Chains},
author = {Moyano, J. M. and Gibaja, E. and Ventura, S.},
url = {https://ieeexplore.ieee.org/abstract/document/7969548/},
doi = {10.1109/CEC.2017.7969548},
year = {2017},
date = {2017-06-01},
booktitle = {2017 IEEE Congress on Evolutionary Computation (CEC)},
pages = {2015-2021},
keywords = {Evolutionary Algorithms, Multi-label Learning, Supervised Learning},
pubstate = {published},
tppubtype = {inproceedings}
}
|
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 @inproceedings{FJMaestre-IWANN-2017,
title = {An Iterated Greedy Algorithm for Improving the Generation of Synthetic Patterns in Imbalanced Learning},
author = {Maestre-Garc\^{i}a, F.J. and Garc\^{i}a-Mart\^{i}nez, C. and P'{e}rez-Ort\^{i}z, M. and Guti'{e}rrez, P.A.},
year = {2017},
date = {2017-05-18},
booktitle = {Proceedings of the International Work-Conference on Artificial Neural Networks: Advances in Computational Intelligence},
pages = {513-524},
address = {Cadiz, Spain},
series = {IWANN 2017},
keywords = {Classification, Metaheuristics, Supervised Learning},
pubstate = {published},
tppubtype = {inproceedings}
}
|
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 @article{2017-INS-MTR,
title = {Multi-Target Support Vector Regression Via Correlation Regressor Chains},
author = {Melki, G. and Cano, A. and Kecman, V. and Ventura, S.},
url = {http://dx.doi.org/10.1016/j.ins.2017.06.017},
doi = {10.1016/j.ins.2017.06.017},
year = {2017},
date = {2017-01-01},
journal = {Information Sciences},
volume = {415-416},
pages = {53-69},
keywords = {Multi-label Learning, Supervised Learning},
pubstate = {published},
tppubtype = {article}
}
|
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 @inproceedings{2017-HAIS,
title = {Sentiment Classification from Multi-class Imbalanced Twitter Data Using Binarization},
author = {Krawczyk, B. and McInnes, B. and Cano, A.},
year = {2017},
date = {2017-01-01},
booktitle = {Proceedings of the 12th International Conference on Hybrid Artificial Intelligent Systems},
pages = {26-37},
keywords = {Classification, Supervised Learning},
pubstate = {published},
tppubtype = {inproceedings}
}
|
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 @article{Cano-2016-SOCO,
title = {ur-CAIM: improved CAIM discretization for unbalanced and balanced data},
author = {Cano, A. and Nguyen, D. T. and Ventura, S. and Cios, K. J.},
url = {http://dx.doi.org/10.1007/s00500-014-1488-1},
doi = {10.1007/s00500-014-1488-1},
year = {2016},
date = {2016-01-01},
journal = {Soft Computing},
volume = {20},
number = {1},
pages = {173-188},
keywords = {Classification, Supervised Learning},
pubstate = {published},
tppubtype = {article}
}
|
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 @inproceedings{Fuentes-Alventosa2016,
title = {Predicci\'{o}n de la aceptaci\'{o}n o rechazo de las calificaciones finales propuestas por el alumnado usando t'{e}cnicas de Miner\^{i}a de Datos},
author = {Fuentes-Alventosa, J. and Romero, C. and Garc\^{i}a-Mart\^{i}nez, C. and Ventura, S.},
url = {http://www.aenui.net/ojs/index.php?journal=actas_jenui&page=article&op=view&path%5B%5D=252},
isbn = {9788416642304},
year = {2016},
date = {2016-01-01},
booktitle = {Actas de las XXII Jornadas sobre la Ense\~{n}anza Universitaria de la Inform\'{a}tica (JENUI 2016)},
pages = {201--208},
keywords = {Classification, Educational Data Mining, Predicting Student Performance, Supervised Learning},
pubstate = {published},
tppubtype = {inproceedings}
}
|
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 @article{reyes2016effective,
title = {Effective lazy learning algorithm based on a data gravitation model for multi-label learning},
author = {Reyes, O. and Morell, C. and Ventura, S.},
url = {http://www.sciencedirect.com/science/article/pii/S0020025516000086},
year = {2016},
date = {2016-01-01},
journal = {Information Sciences},
volume = {340},
number = {341},
pages = {159-174},
publisher = {Elsevier},
keywords = {Multi-label Learning, Supervised Learning},
pubstate = {published},
tppubtype = {article}
}
|
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 @inproceedings{Moyano2015b_CAEPIA,
title = {Dise\~{n}o autom\'{a}tico de multi-clasificadores basados en proyecciones de etiquetas},
author = {Moyano, J. M. and Gibaja, E. and Cano, A. and Luna, J. M. and Ventura, S.},
url = {http://simd.albacete.org/actascaepia15/papers/00355.pdf},
year = {2015},
date = {2015-01-01},
booktitle = {XVI Conferencia de la Asociaci\'{o}n Espa\~{n}ola para la Inteligencia Artificial},
pages = {355--365},
series = {CAEPIA'15},
keywords = {Classification, Evolutionary Algorithms, Multi-label Learning, Supervised Learning},
pubstate = {published},
tppubtype = {inproceedings}
}
|
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 @inproceedings{Moyano-2015-MAEB,
title = {Algoritmo evolutivo para optimizar ensembles de clasificadores multi-etiqueta},
author = {Moyano, J. M. and Gibaja, E. and Cano, A. and Luna, J. M. and Ventura, S.},
url = {http://www.uco.es/~i02momuj/pdf/maeb15.pdf},
year = {2015},
date = {2015-01-01},
booktitle = {X Congreso Espa\~{n}ol sobre Metaheur\^{i}sticas and Algoritmos Evolutivos y Bioinspirados},
pages = {219-225},
series = {MAEB'15},
keywords = {Classification, Evolutionary Algorithms, Multi-label Learning, Supervised Learning},
pubstate = {published},
tppubtype = {inproceedings}
}
|
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 @article{Reyes-2015-NEUCOM,
title = {Scalable extensions of the ReliefF algorithm for weighting and selecting features on the multi-label learning context},
author = {Reyes, O. and Morell, C. and Ventura, S.},
url = {http://dx.doi.org/10.1016/j.neucom.2015.02.045},
doi = {10.1016/j.neucom.2015.02.045},
year = {2015},
date = {2015-01-01},
journal = {Neurocomputing},
volume = {161},
pages = {168--182},
keywords = {Data Preprocessing, Feature Selection, Multi-label Learning, Supervised Learning},
pubstate = {published},
tppubtype = {article}
}
|
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 @inproceedings{Fuentes-Alventosa2014,
title = {Accepting or Rejecting Students' Self-grading in Their Final Marks by using Data Mining},
author = {Fuentes-Alventosa, J. and Romero, C. and Garc\^{i}a-Mart\^{i}nez, C. and Ventura, S.},
url = {http://educationaldatamining.org/EDM2014/uploads/procs2014/posters/3_EDM-2014-Poster.pdf},
year = {2014},
date = {2014-01-01},
booktitle = {International Conference on Educational Data Mining (EDM'14)},
pages = {327--328},
keywords = {Classification, Educational Data Mining, Predicting Student Performance, Supervised Learning},
pubstate = {published},
tppubtype = {inproceedings}
}
|
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 @inproceedings{Pedraza2014,
title = {Classification Rule Mining with Iterated Greedy},
author = {Pedraza, J. A. and Garc\^{i}a-Mart\^{i}nez, C. and Cano, A. and Ventura, S.},
url = {http://link.springer.com/chapter/10.1007/978-3-319-07617-1_51},
year = {2014},
date = {2014-01-01},
booktitle = {International Conference on Hybrid Artificial Intelligence Systems},
pages = {585--596},
keywords = {Classification, Supervised Learning},
pubstate = {published},
tppubtype = {inproceedings}
}
|
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 @article{Reyes-2014-ICAE,
title = {Evolutionary feature weighting to improve the performance of multi-label lazy algorithms},
author = {Reyes, O. and Morell, C. and Ventura, S.},
url = {http://dx.doi.org/10.3233/ICA-140468},
doi = {10.3233/ICA-140468},
year = {2014},
date = {2014-01-01},
journal = {Integrated Computer-Aided Engineering},
volume = {21},
number = {4},
pages = {339-354},
keywords = {Data Preprocessing, Evolutionary Algorithms, Multi-label Learning, Supervised Learning},
pubstate = {published},
tppubtype = {article}
}
|
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 @inproceedings{Pupo2013,
title = {ReliefF-ML: An Extension of ReliefF Algorithm to Multi-label Learning},
author = {Reyes, O. and Morell, C. and Ventura, S.},
editor = {Ruiz-Shulcloper, J. and Sanniti di Baja, G.},
url = {http://dx.doi.org/10.1007/978-3-642-41827-3_66},
year = {2013},
date = {2013-01-01},
booktitle = {Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications: 18th Iberoamerican Congress (CIARP-2013), Havana, Cuba, November 20-23, 2013, Proceedings, Part II},
pages = {528-535},
publisher = {Springer Berlin Heidelberg},
keywords = {Data Preprocessing, Multi-label Learning, Supervised Learning},
pubstate = {published},
tppubtype = {inproceedings}
}
|
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 @inproceedings{reyes2013quadratic,
title = {Feature weighting on multi-label data through quadratic loss minimization},
author = {Reyes, O. and Morell, C. and Ventura, S.},
url = {http://www.compumat.uci.cu/},
year = {2013},
date = {2013-01-01},
booktitle = {Congreso Internacional de Matem\'{a}tica y Computaci\'{o}n (COMPUMAT-2013)},
keywords = {Data Preprocessing, Evolutionary Algorithms, Multi-label Learning, Supervised Learning},
pubstate = {published},
tppubtype = {inproceedings}
}
|
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 @inproceedings{Reyes-2012-ISDA,
title = {Learning similarity metric to improve the performance of lazy multi-label ranking algorithms},
author = {Reyes, O. and Morell, C. and Ventura, S.},
url = {http://dx.doi.org/10.1109/ISDA.2012.6416545},
doi = {10.1109/ISDA.2012.6416545},
year = {2012},
date = {2012-01-01},
booktitle = {Proceedings of the 12th International Conference on Intelligent Systems Design and Applications, ISDA'12},
pages = {246-251},
keywords = {Data Preprocessing, Evolutionary Algorithms, Multi-label Learning, Supervised Learning},
pubstate = {published},
tppubtype = {inproceedings}
}
|
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 @inproceedings{Olmo-2010-MAEB,
title = {Miner\^{i}a de Reglas de Clasificaci\'{o}n mediante un Algoritmo de Programaci\'{o}n Autom\'{a}tica con Hormigas},
author = {Olmo, J. L. and Luna, J. M. and Romero, J. R. and Ventura, S.},
year = {2010},
date = {2010-01-01},
booktitle = {VII Congreso Espa\~{n}ol sobre Metaheur\^{i}sticas and Algoritmos Evolutivos y Bioinspirados},
pages = {243-250},
address = {Valencia, Espa\~{n}a},
series = {MAEB 2010},
keywords = {Ant Programming, Bioinspired algorithms, Classification, Evolutionary Algorithms, Supervised Learning},
pubstate = {published},
tppubtype = {inproceedings}
}
|
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 @inproceedings{Olmo-2010-PAAMS,
title = {An Automatic Programming ACO-Based Algorithm for Classification Rule Mining},
author = {Olmo, J. L. and Luna, J. M. and Romero, J. R. and Ventura, S.},
url = {http://link.springer.com/chapter/10.1007%2F978-3-642-12433-4_76},
doi = {10.1007/978-3-642-12433-4_76},
year = {2010},
date = {2010-01-01},
booktitle = {Proceedings of the 8th International Conference on Practical Applications of Agents and Multiagent Systems},
pages = {649--656},
address = {Salamanca, Spain},
series = {PAAMS 2010},
keywords = {Ant Programming, Bioinspired algorithms, Classification, Evolutionary Algorithms, Supervised Learning},
pubstate = {published},
tppubtype = {inproceedings}
}
|