Julián Luengo Martín

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Francisco HerreraProfessor Computer Science and AI, Granada University, SpainDirección de correo verificada de decsai.ugr.es
Salvador GarcíaFull Professor of Computer Science and Artificial Intelligence. University of Granada.Dirección de correo verificada de decsai.ugr.es
Alberto FernándezAssociate Professor in Computer Science and Artificial Intelligence, University of GranadaDirección de correo verificada de decsai.ugr.es
José A. SáezDept. of Statistics and Operations Research, University of GranadaDirección de correo verificada de ugr.es
Joaquin Derrac RusData ScientistDirección de correo verificada de gresearch.co.uk
Diego García-GilAssistant Professor, University of GranadaDirección de correo verificada de ugr.es
Sergio Ramírez-GallegoPhD. ML and Computer ScienceDirección de correo verificada de thalesaleniaspace.com
Luciano SanchezProfessor of Computer Science, Oviedo UniversityDirección de correo verificada de uniovi.es
Isaac Triguero VelázquezDistinguished Senior Research Fellow at University of Granada, Associate Professor in Data ScienceDirección de correo verificada de nottingham.ac.uk
Anabel Gómez-RíosUniversidad de GranadaDirección de correo verificada de decsai.ugr.es
Jesus Alcala-FdezAssociate Professor of Computer Science and Artificial Intelligence, University of GranadaDirección de correo verificada de decsai.ugr.es
Siham TabikAssociate Professor, Dpt. Computer Science and Artificial Intelligence, University of GranadaDirección de correo verificada de ugr.es
Mikel GalarAssociate Professor of Computer Science and Artificial Intelligence, Universidad Pública de NavarraDirección de correo verificada de unavarra.es
Jesús Maillo HidalgoPh.D. Department of Computer Science and Artificial Intelligence, University of GranadaDirección de correo verificada de decsai.ugr.es
Victoria Lopez MoralesResearch Associate, Imperial College LondonDirección de correo verificada de imperial.ac.uk
José Ramón Cano De AmoUniversity of JaenDirección de correo verificada de ujaen.es
Sergio González VázquezPhD on Information & Communications Technology. Department of Computer Science and ArtificialDirección de correo verificada de decsai.ugr.es
Jerzy StefanowskiPoznan University of TechnologyDirección de correo verificada de cs.put.poznan.pl
María José Del Jesus DíazAssociate professor of Computer Science, University of JaénDirección de correo verificada de ujaen.es
ASM ShihavuddinProfessor, EEE, Green University of Bangladesh (GUB)Dirección de correo verificada de eee.green.edu.bd

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Julián Luengo Martín

Associate Professor at University of Granada

Dirección de correo verificada de decsai.ugr.es

Artificial Intelligence Data Preprocessing in Data mining Missing Values Noise Data Data Complexity


Título Ordenar por citas Ordenar por año Ordenar por título	Citado por Citado por	Año
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, 2015	2638	2015
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	1944	2010
Data Preprocessing in Data Mining S García, J Luengo, F Herrera Springer, 2014	1286	2014
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	728	2009
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	593	2012
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	496	2015
Big data preprocessing: methods and prospects S García, S Ramírez-Gallego, J Luengo, JM Benítez, F Herrera Big Data Analytics 1 (1), 1-22, 2016	492	2016
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	283	2016
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	283	2012
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	278	2020
KEEL 3.0: an open source software for multi-stage analysis in data mining I Triguero, S González, JM Moyano, S García López, J Alcalá Fernández, ... Atlantis Press, 2017	231	2017
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	192	2011
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	186	2010
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	176	2009
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	146	2014
Enabling smart data: noise filtering in big data classification D García-Gil, J Luengo, S García, F Herrera Information Sciences 479, 135-152, 2019	141	2019
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	121	2019
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	118	2013
A study on the use of imputation methods for experimentation with radial basis function network classifiers handling missing attribute values: The good synergy between rbfns … J Luengo, S García, F Herrera Neural Networks 23 (3), 406-418, 2010	115	2010
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	109	2019

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