2022
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Pérez, E; Ventura, S An ensemble-based convolutional neural network model powered by a genetic algorithm for melanoma diagnosis Journal Article Neural Computing and Applications, 34 (13), pp. 10429–10448, 2022. Links | BibTeX | Tags: Cancer, Data Preprocessing, Data Science, Deep Learning, Evolutionary Algorithms, Genetic Algorithms, Medical Data Mining, Melanoma Diagnosis, Special Issue @article{perez2022ensemble,
title = {An ensemble-based convolutional neural network model powered by a genetic algorithm for melanoma diagnosis},
author = {P'{e}rez, E. and Ventura, S.},
url = {https://link.springer.com/article/10.1007/s00521-021-06655-7},
year = {2022},
date = {2022-01-01},
journal = {Neural Computing and Applications},
volume = {34},
number = {13},
pages = {10429--10448},
publisher = {Springer},
keywords = {Cancer, Data Preprocessing, Data Science, Deep Learning, Evolutionary Algorithms, Genetic Algorithms, Medical Data Mining, Melanoma Diagnosis, Special Issue},
pubstate = {published},
tppubtype = {article}
}
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Ramírez, A; Feldt, R; Romero, J R A Taxonomy of Information Attributes for Test Case Prioritisation: Applicability, Machine Learning Journal Article ACM Transactions on Software Engineering and Methodology, 2022. Links | BibTeX | Tags: Data Preprocessing, Predictive Models, Software analytics @article{ramirez2022taxonomy,
title = {A Taxonomy of Information Attributes for Test Case Prioritisation: Applicability, Machine Learning},
author = {Ram\^{i}rez, A. and Feldt, R. and Romero, J. R.},
url = {https://dl.acm.org/doi/10.1145/3511805},
doi = {10.1145/3511805},
year = {2022},
date = {2022-01-01},
journal = {ACM Transactions on Software Engineering and Methodology},
publisher = {Association for Computing Machinery},
keywords = {Data Preprocessing, Predictive Models, Software analytics},
pubstate = {published},
tppubtype = {article}
}
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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}
}
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Moyano, J M; Luna, J M; Ventura, S Improving the Performance of Multi-Label Classifiers via Label Space Reduction Inproceedings 2022 IEEE International Conference on Omni-layer Intelligent Systems (COINS), pp. 1–6, IEEE 2022. BibTeX | Tags: Data Preprocessing, Multi-label Learning @inproceedings{moyano2022improving,
title = {Improving the Performance of Multi-Label Classifiers via Label Space Reduction},
author = {Moyano, J. M. and Luna, J. M. and Ventura, S.},
year = {2022},
date = {2022-01-01},
booktitle = {2022 IEEE International Conference on Omni-layer Intelligent Systems (COINS)},
pages = {1--6},
organization = {IEEE},
keywords = {Data Preprocessing, Multi-label Learning},
pubstate = {published},
tppubtype = {inproceedings}
}
|
2021
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Pérez, E; Ventura, S Melanoma Recognition by Fusing Convolutional Blocks and Dynamic Routing between Capsules Journal Article Cancers, 13 (19), pp. 4974, 2021. Links | BibTeX | Tags: Cancer, Data Preprocessing, Data Science, Deep Learning, Medical Data Mining, Melanoma Diagnosis, Special Issue @article{perez2021melanoma,
title = {Melanoma Recognition by Fusing Convolutional Blocks and Dynamic Routing between Capsules},
author = {P'{e}rez, E. and Ventura, S.},
url = {https://www.mdpi.com/2072-6694/13/19/4974},
doi = {10.3390/cancers13194974},
year = {2021},
date = {2021-01-01},
journal = {Cancers},
volume = {13},
number = {19},
pages = {4974},
publisher = {MDPI},
keywords = {Cancer, Data Preprocessing, Data Science, Deep Learning, Medical Data Mining, Melanoma Diagnosis, Special Issue},
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
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Pérez, E; Reyes, O; Ventura, S Convolutional neural networks for the automatic diagnosis of melanoma: An extensive experimental study Journal Article Medical image analysis, 67 , pp. 101858, 2020. Links | BibTeX | Tags: Cancer, Data Preprocessing, Data Science, Deep Learning, Medical Data Mining, Melanoma Diagnosis @article{Perez2020,
title = {Convolutional neural networks for the automatic diagnosis of melanoma: An extensive experimental study},
author = {P'{e}rez, E. and Reyes, O. and Ventura, S.},
url = {https://www.sciencedirect.com/science/article/pii/S136184152030222X},
year = {2020},
date = {2020-01-01},
journal = {Medical image analysis},
volume = {67},
pages = {101858},
publisher = {Elsevier},
keywords = {Cancer, Data Preprocessing, Data Science, Deep Learning, Medical Data Mining, Melanoma Diagnosis},
pubstate = {published},
tppubtype = {article}
}
|
Reyes, O; Pérez, E; Luque, R; Castaño, J; Ventura, S A supervised machine learning-based methodology for analyzing dysregulation in splicing machinery: An application in cancer diagnosis Journal Article Artificial Intelligence in Medicine, 108 , pp. 101950, 2020. Links | BibTeX | Tags: Cancer, Data Preprocessing, Data Science, Medical Data Mining, Melanoma Diagnosis @article{Reyes2020,
title = {A supervised machine learning-based methodology for analyzing dysregulation in splicing machinery: An application in cancer diagnosis},
author = {Reyes, O. and P'{e}rez, E. and Luque, R. and Casta\~{n}o, J. and Ventura, S.},
url = {https://www.sciencedirect.com/science/article/pii/S0933365719312187},
year = {2020},
date = {2020-01-01},
journal = {Artificial Intelligence in Medicine},
volume = {108},
pages = {101950},
publisher = {Elsevier},
keywords = {Cancer, Data Preprocessing, Data Science, Medical Data Mining, Melanoma Diagnosis},
pubstate = {published},
tppubtype = {article}
}
|
2017
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Moyano, J M; Gibaja, E; Ventura, S MLDA: A tool for analyzing multi-label datasets Journal Article Knowledge-Based Systems, 121 , pp. 1-3, 2017, ISSN: 0950-7051. Links | BibTeX | Tags: Data Mining Software, Data Preprocessing, Multi-label Learning, Multi-view Learning @article{Moyano-2016-KBS,
title = {MLDA: A tool for analyzing multi-label datasets},
author = {Moyano, J. M. and Gibaja, E. and Ventura, S.},
url = {http://dx.doi.org/10.1007/10.1016/j.knosys.2017.01.018},
doi = {10.1016/j.knosys.2017.01.018},
issn = {0950-7051},
year = {2017},
date = {2017-01-01},
journal = {Knowledge-Based Systems},
volume = {121},
pages = {1-3},
keywords = {Data Mining Software, Data Preprocessing, Multi-label Learning, Multi-view Learning},
pubstate = {published},
tppubtype = {article}
}
|
2016
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Moyano, J M; Gibaja, E; Ventura, S Una herramienta para analizar conjuntos de datos multi-etiqueta Inproceedings XVII Conferencia de la Asociación Española para la Inteligencia Artificial, CAEPIA '16, pp. 857–866, 2016, ISBN: 978-84-9012-632-5. Links | BibTeX | Tags: Data Preprocessing, Feature Selection, Instance Selection, Multi-label Learning, Multi-view Learning, Software Design and Development @inproceedings{Moyano2016b_CAEPIA,
title = {Una herramienta para analizar conjuntos de datos multi-etiqueta},
author = {Moyano, J. M. and Gibaja, E. and Ventura, S.},
url = {http://www.uco.es/~i02momuj/pdf/caepia16.pdf},
isbn = {978-84-9012-632-5},
year = {2016},
date = {2016-01-01},
booktitle = {XVII Conferencia de la Asociaci\'{o}n Espa\~{n}ola para la Inteligencia Artificial, CAEPIA '16},
pages = {857--866},
keywords = {Data Preprocessing, Feature Selection, Instance Selection, Multi-label Learning, Multi-view Learning, Software Design and Development},
pubstate = {published},
tppubtype = {inproceedings}
}
|
2015
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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
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Cano, A; Ventura, S; Cios, K J Scalable CAIM discretization on multiple GPUs using concurrent kernels Journal Article Journal of Supercomputing, 69 (1), pp. 273-292, 2014. Links | BibTeX | Tags: Classification, Data Preprocessing, GP-GPU @article{Cano-2014-JSUP,
title = {Scalable CAIM discretization on multiple GPUs using concurrent kernels},
author = {Cano, A. and Ventura, S. and Cios, K. J.},
url = {http://dx.doi.org/10.1007/s11227-014-1151-8},
doi = {10.1007/s11227-014-1151-8},
year = {2014},
date = {2014-01-01},
journal = {Journal of Supercomputing},
volume = {69},
number = {1},
pages = {273-292},
keywords = {Classification, Data Preprocessing, GP-GPU},
pubstate = {published},
tppubtype = {article}
}
|
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}
}
|
Romero, C; Romero, J R; Ventura, S A survey on pre-processing educational data Journal Article Studies in Computational Intelligence, 524 , pp. 29-64, 2014. Links | BibTeX | Tags: Data Preprocessing, Educational Data Mining @article{Romero-2014-SCI,
title = {A survey on pre-processing educational data},
author = {Romero, C. and Romero, J. R. and Ventura, S.},
url = {http://dx.doi.org/10.1007/978-3-319-02738-8-2},
doi = {10.1007/978-3-319-02738-8-2},
year = {2014},
date = {2014-01-01},
journal = {Studies in Computational Intelligence},
volume = {524},
pages = {29-64},
keywords = {Data Preprocessing, Educational Data Mining},
pubstate = {published},
tppubtype = {article}
}
|
2013
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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}
}
|