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Julián Luengo Martín
Julián Luengo Martín
Associate Professor at University of Granada
Email verificata su decsai.ugr.es
Titolo
Citata da
Citata da
Anno
Keel data-mining software tool: Data set repository, integration of algorithms and experimental analysis framework
J Derrac, S Garcia, L Sanchez, F Herrera
J. Mult. Valued Logic Soft Comput 17, 255-287, 2015
29552015
Advanced nonparametric tests for multiple comparisons in the design of experiments in computational intelligence and data mining: Experimental analysis of power
S García, A Fernández, J Luengo, F Herrera
Information sciences 180 (10), 2044-2064, 2010
22782010
Data Preprocessing in Data Mining
S García, J Luengo, F Herrera
Springer, 2014
17722014
A study of statistical techniques and performance measures for genetics-based machine learning: accuracy and interpretability
S García, A Fernández, J Luengo, F Herrera
Soft Computing 13, 959-977, 2009
8012009
Big data preprocessing: methods and prospects
S García, S Ramírez-Gallego, J Luengo, JM Benítez, F Herrera
Big data analytics 1, 1-22, 2016
7742016
A survey of discretization techniques: Taxonomy and empirical analysis in supervised learning
S Garcia, J Luengo, JA Sáez, V Lopez, F Herrera
IEEE transactions on Knowledge and Data Engineering 25 (4), 734-750, 2012
6902012
SMOTE–IPF: Addressing the noisy and borderline examples problem in imbalanced classification by a re-sampling method with filtering
JA Sáez, J Luengo, J Stefanowski, F Herrera
Information Sciences 291, 184-203, 2015
6302015
COVIDGR dataset and COVID-SDNet methodology for predicting COVID-19 based on chest X-ray images
S Tabik, A Gómez-Ríos, JL Martín-Rodríguez, I Sevillano-García, ...
IEEE journal of biomedical and health informatics 24 (12), 3595-3605, 2020
4102020
Tutorial on practical tips of the most influential data preprocessing algorithms in data mining
S García, J Luengo, F Herrera
Knowledge-Based Systems 98, 1-29, 2016
3602016
On the choice of the best imputation methods for missing values considering three groups of classification methods
J Luengo, S García, F Herrera
Knowledge and information systems 32, 77-108, 2012
3262012
KEEL 3.0: an open source software for multi-stage analysis in data mining
I Triguero, S González, JM Moyano, S García, J Alcalá-Fdez, J Luengo, ...
International Journal of Computational Intelligence Systems 10 (1), 1238-1249, 2017
2902017
Transforming big data into smart data: An insight on the use of the k‐nearest neighbors algorithm to obtain quality data
I Triguero, D García‐Gil, J Maillo, J Luengo, S García, F Herrera
Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery 9 (2 …, 2019
2442019
Addressing data complexity for imbalanced data sets: analysis of SMOTE-based oversampling and evolutionary undersampling
J Luengo, A Fernández, S García, F Herrera
Soft Computing 15, 1909-1936, 2011
2332011
Genetics-based machine learning for rule induction: state of the art, taxonomy, and comparative study
A Fernández, S García, J Luengo, E Bernadó-Mansilla, F Herrera
IEEE Transactions on Evolutionary Computation 14 (6), 913-941, 2010
2022010
A study on the use of statistical tests for experimentation with neural networks: Analysis of parametric test conditions and non-parametric tests
J Luengo, S García, F Herrera
Expert Systems with Applications 36 (4), 7798-7808, 2009
1972009
Keel data-mining software tool: Data set repository, integration of algorithms and experimental analysis framework
J Alcal-Fdez, A Fernndez, J Luengo, J Derrac, S Garca, L Snchez, ...
Journal of Multiple-Valued Logic and Soft Computing 17 (2-3), 255-287, 2011
1812011
Enabling smart data: noise filtering in big data classification
D García-Gil, J Luengo, S García, F Herrera
Information Sciences 479, 135-152, 2019
1792019
Analyzing the presence of noise in multi-class problems: alleviating its influence with the one-vs-one decomposition
JA Sáez, M Galar, J Luengo, F Herrera
Knowledge and information systems 38, 179-206, 2014
1722014
Towards highly accurate coral texture images classification using deep convolutional neural networks and data augmentation
A Gómez-Ríos, S Tabik, J Luengo, ASM Shihavuddin, B Krawczyk, ...
Expert Systems with Applications 118, 315-328, 2019
1612019
Tackling the problem of classification with noisy data using multiple classifier systems: Analysis of the performance and robustness
JA Sáez, M Galar, J Luengo, F Herrera
Information Sciences 247, 1-20, 2013
1392013
Il sistema al momento non può eseguire l'operazione. Riprova più tardi.
Articoli 1–20