Julián Luengo Martín

Categoría

Doctor

Contacto

julianlm@Qj2HqxRwdecsai.ugr.es

Organismo

UGR

Highly Cited Researcher en el año Ver CV


Researcher Profile

Total Desde 2016:
Citas Total: 9443 Desde 2016: 7182
Índice H Total: 30 Desde 2016: 29
Índice i10 Total: 56 Desde 2016: 47

Publicaciones (126)

Título Autores Año
Multiple instance classification: Bag noise filtering for negative instance noise cleaning J Luengo, D Sánchez-Tarragó, RC Prati, F Herrera. 2021
A tutorial on the segmentation of metallographic images: Taxonomy, new MetalDAM dataset, deep learning-based ensemble model, experimental analysis and challenges J Luengo, R Moreno, I Sevillano, D Charte, A Peláez-Vegas, .... 2021
A robust approach for deep neural networks in presence of label noise: relabelling and filtering instances during training A Gómez-Ríos, J Luengo, F Herrera. 2021
Anomaly Detection in Predictive Maintenance: A New Evaluation Framework for Temporal Unsupervised Anomaly Detection Algorithms J Carrasco, I Markova, D López, I Aguilera, D García, M García-Barzana, .... 2021
Enhancing instance-level constrained clustering through differential evolution G González-Almagro, J Luengo, JR Cano, S García. 2021
ME-MEOA/DCC: Multiobjective constrained clustering through decomposition-based memetic elitism G González-Almagro, A Rosales-Pérez, J Luengo, JR Cano, S García. 2021
Similarity-based and Iterative Label Noise Filters for Monotonic Classification JR Cano, J Luengo, S García. 2020
Reconstrucciones “Resilientes” de la Identidad Profesional del Profesorado: Endoprivatización y Cultura Performativa en Andalucía (España) J Molina-Pérez, J Luengo. 2020
Big Data: Technologies and Tools J Luengo, D García-Gil, S Ramírez-Gallego, S García, F Herrera. 2020
Smart Data J Luengo, D García-Gil, S Ramírez-Gallego, S García, F Herrera. 2020
Final Thoughts: From Big Data to Smart Data J Luengo, D García-Gil, S Ramírez-Gallego, S García, F Herrera. 2020
Big Data Discretization J Luengo, D García-Gil, S Ramírez-Gallego, S García, F Herrera. 2020
Imbalanced Data Preprocessing for Big Data J Luengo, D García-Gil, S Ramírez-Gallego, S García, F Herrera. 2020
Big Data Software J Luengo, D García-Gil, S Ramírez-Gallego, S García, F Herrera. 2020
Dimensionality Reduction for Big Data J Luengo, D García-Gil, S Ramírez-Gallego, S García, F Herrera. 2020
Data Reduction for Big Data J Luengo, D García-Gil, S Ramírez-Gallego, S García, F Herrera. 2020
Big Data Preprocessing: Enabling Smart Data J Luengo. 2020
Imperfect Big Data J Luengo, D García-Gil, S Ramírez-Gallego, S García, F Herrera. 2020
DILS: constrained clustering through Dual Iterative Local Search G González-Almagro, J Luengo, JR Cano, S García. 2020
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, .... 2020
Improving constrained clustering via decomposition-based multiobjective optimization with memetic elitism G González-Almagro, A Rosales-Pérez, J Luengo, JR Cano, S García. 2020
Synthetic Sample Generation for Label Distribution Learning M González, J Luengo, JR Cano, S García. 2020
Agglomerative Constrained Clustering Through Similarity and Distance Recalculation G González-Almagro, JL Suarez, J Luengo, JR Cano, S García. 2020
Smartdata: data preprocessing to achieve smart data in R I Cordón, J Luengo, S García, F Herrera, F Charte. 2019
Label noise filtering techniques to improve monotonic classification JR Cano, J Luengo, S García. 2019
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, .... 2019
Redes Neuronales Convolucionales para Una Clasificacion Precisa de Imágenes de Corales A Gómez-Rıos, S Tabik, J Luengo, F Herrera, ASM Shihavuddin, .... 2019
Enabling smart data: noise filtering in big data classification D García-Gil, J Luengo, S García, F Herrera. 2019
Emerging topics and challenges of learning from noisy data in nonstandard classification: a survey beyond binary class noise RC Prati, J Luengo, F Herrera. 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. 2019
Coral species identification with texture or structure images using a two-level classifier based on Convolutional Neural Networks A Gómez-Ríos, S Tabik, J Luengo, ASM Shihavuddin, F Herrera. 2019
Fast and Scalable Approaches to Accelerate the Fuzzy k Nearest Neighbors Classifier for Big Data J Maillo, I Triguero, J Luengo, FH S. García. 2019
From Big to Smart Data: Iterative Ensemble Filter for Noise Filtering in Big Data classification FH Diego Garcia, Francisco Luque-Sánchez, Julián Luengo, Salvador García. 2019
Preprocessing methodology for time series: an industrial world application case study JA Cortés-Ibáñez, S González, JJ Valle-Alonso, J Luengo, S García, .... 2019
Big Data Preprocessing as the Bridge between Big Data and Smart Data: BigDaPSpark and BigDaPFlink Libraries D Garcıa-Gil, A Alcalde-Barros, J Luengo, S Garcıa, F Herrera. 2019
Fast and Scalable Approaches to Accelerate the Fuzzy k-Nearest Neighbors Classifier for Big Data J Maillo, S García, J Luengo, F Herrera, I Triguero. 2019
Big Data Preprocessing as the Bridge between Big Data and Smart Data: BigDaPSpark and BigDaPFlink Libraries. D García-Gil, A Alcalde-Barros, J Luengo, S García, F Herrera. 2019
CNC-NOS: Class noise cleaning by ensemble filtering and noise scoring J Luengo, SO Shim, S Alshomrani, A Altalhi, F Herrera. 2018
A preliminary study on Hybrid Spill-Tree Fuzzy k-Nearest Neighbors for big data classification J Maillo, J Luengo, S García, F Herrera, I Triguero. 2018
A First Study on the Use of Noise Filtering to Clean the Bags in Multi-Instance Classification J Luengo, D Sánchez-Tarragó, RC Prati, F Herrera. 2018
Un enfoque aproximado para acelerar el algoritmo de clasificacion Fuzzy kNN para Big Data J Maillo, J Luengo, S Garcıa, F Herrera, I Triguero. 2018
Smart Data: Filtrado de Ruido para Big Data DJG Gil, J Luengo, SG Gil, F Herrera. 2018
Task Recommendation for Group Users in Public IoT Environments JS Lee, MH Kim, IY Ko. 2018
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, .... 2017
Exact fuzzy k-nearest neighbor classification for big datasets J Maillo, J Luengo, S García, F Herrera, I Triguero. 2017
A study on the noise label influence in boosting algorithms: AdaBoost, GBM and XGBoost A Gómez-Ríos, J Luengo, F Herrera. 2017
The noisefiltersr package: label noise preprocessing in R P Morales, J Luengo, LPF Garcia, AC Lorena, AC de Carvalho, F Herrera. 2017
The NoiseFiltersR Package: Label Noise Preprocessing in R. P Morales, J Luengo, LPF Garcia, AC Lorena, AC de Carvalho, F Herrera. 2017
Protestando en Twitter: ciudadanía y empoderamiento desde la educación pública= Protesting on Twitter: Citizenship and Empowerment from Public Education G Saura, JL Muñoz, J Luengo, JM Martos. 2017
The influence of noise on the evolutionary fuzzy systems for subgroup discovery J Luengo, AM García-Vico, MD Pérez-Godoy, CJ Carmona. 2016
Tutorial on practical tips of the most influential data preprocessing algorithms in data mining S García, J Luengo, F Herrera. 2016
Big data preprocessing: methods and prospects S García, S Ramírez-Gallego, J Luengo, JM Benítez, F Herrera. 2016
INFFC: an iterative class noise filter based on the fusion of classifiers with noise sensitivity control JA Sáez, M Galar, J Luengo, F Herrera. 2016
Evaluating the classifier behavior with noisy data considering performance and robustness: The equalized loss of accuracy measure JA Sáez, J Luengo, F Herrera. 2016
From big data to smart data with the k-nearest neighbours algorithm I Triguero, J Maillo, J Luengo, S García, F Herrera. 2016
A first study on the use of boosting for class noise reparation PM Álvarez, J Luengo, F Herrera. 2016
Comparison of KEEL versus open source Data Mining tools: Knime and Weka software I Triguero, S González, JM Moyano, S García, J Alcala-Fdez, J Luengo, .... 2016
Mixtures of Polynomials for Regression Problems JC Luengo, R Rumi. 2016
Package ‘NoiseFiltersR’ P Morales, J Luengo, LPF Garcia, AC Lorena, AC de Carvalho, F Herrera, .... 2016
A first approach in the class noise filtering approaches for fuzzy subgroup discovery CJ Carmona, J Luengo. 2015
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. 2015
Using the One-vs-One decomposition to improve the performance of class noise filters via an aggregation strategy in multi-class classification problems LPF Garcia, JA Sáez, J Luengo, AC Lorena, AC de Carvalho, F Herrera. 2015
An automatic extraction method of the domains of competence for learning classifiers using data complexity measures J Luengo, F Herrera. 2015
Naive Bayes classifier with mixtures of polynomials J Luengo, R Rumi. 2015
Naive Bayes Classifier with Mixtures of Polynomials. J Luengo, R Rumí. 2015
Data Preprocessing in Data Mining S García, J Luengo, F Herrera. 2014
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. 2014
On the characterization of noise filters for self-training semi-supervised in nearest neighbor classification I Triguero, JA Sáez, J Luengo, S García, F Herrera. 2014
Statistical computation of feature weighting schemes through data estimation for nearest neighbor classifiers JA Sáez, J Derrac, J Luengo, F Herrera. 2014
Managing borderline and noisy examples in imbalanced classification by combining SMOTE with ensemble filtering JA Sáez, J Luengo, J Stefanowski, F Herrera. 2014
Big data analytics B Analytics. 2014
Las políticas y legislación españolas de formación profesional: las consecuencias de la aprobación de la Ley de Cualificaciones y de la Formación Profesional y de la Ley de … M Jiménez, J Luengo, D Sevilla. 2014
Improving the behavior of the nearest neighbor classifier against noisy data with feature weighting schemes JA Sáez, J Derrac, J Luengo, F Herrera. 2014
4. Evaluation measures of the behavior of classifiers with noisy data JA Sáez, J Luengo, F Herrera. 2014
Journal: Intelligent Systems Reference Library Data Preprocessing in Data Mining, 2014, p. 1-17 S García, J Luengo, F Herrera. 2014
Predicting noise filtering efficacy with data complexity measures for nearest neighbor classification JA SáEz, JN Luengo, F Herrera. 2013
Tackling the problem of classification with noisy data using Multiple Classifier Systems: Analysis of the performance and robustness JA SáEz, M Galar, JN Luengo, F Herrera. 2013
An Experimental Case of Study on the Behavior of Multiple Classifier Systems with Class Noise Datasets JA Sáez, M Galar, J Luengo, F Herrera. 2013
Dinámicas endógenas de privatización en la educación. La cultura de la performatividad J Luengo, G Saura. 2013
Nuevas formas de mercantilizar la educación J Luengo, G Saura. 2013
An analysis on the use of pre-processing methods in evolutionary fuzzy systems for subgroup discovery CJ Carmona, J Luengo, P González, MJ Del Jesus. 2012
A Preliminary Study on Selecting the Optimal Cut Points in Discretization by Evolutionary Algorithms. S García, V López, J Luengo, CJ Carmona, F Herrera. 2012
A preliminary study on missing data imputation in evolutionary fuzzy systems of subgroup discovery CJ Carmona, J Luengo, P González, MJ del Jesus. 2012
A survey of discretization techniques: Taxonomy and empirical analysis in supervised learning S Garcia, J Luengo, JA Sáez, V Lopez, F Herrera. 2012
On the choice of the best imputation methods for missing values considering three groups of classification methods J Luengo, S García, F Herrera. 2012
Missing data imputation for fuzzy rule-based classification systems J Luengo, JA Sáez, F Herrera. 2012
Shared domains of competence of approximate learning models using measures of separability of classes J Luengo, F Herrera. 2012
A first study on decomposition strategies with data with class noise using decision trees JA Sáez, M Galar, J Luengo, F Herrera. 2012
On the suitability of fuzzy rule-based classification systems with noisy data J Saez, J Luengo, F Herrera. 2012
La gestión de resultado como mecanismo endógeno de privatización en educación J Luengo, G Saura. 2012
Evolutionary selection of hyperrectangles in nested generalized exemplar learning S García, J Derrac, J Luengo, CJ Carmona, F Herrera. 2011
Keel data-mining software tool: data set repository, integration of algorithms and experimental analysis framework. J Alcalá-Fdez, A Fernández, J Luengo, J Derrac, S García, L Sánchez, .... 2011
Addressing data complexity for imbalanced data sets: analysis of SMOTE-based oversampling and evolutionary undersampling J Luengo, A Fernández, S García, F Herrera. 2011
Fuzzy rule based classification systems versus crisp robust learners trained in presence of class noise's effects: a case of study JA Sáez, J Luengo, F Herrera. 2011
Using KEEL software as a educational tool: A case of study teaching data mining J Derrac, J Luengo, J Alcala-Fdez, A Fernandez, S Garcia. 2011
Imputation of Missing Values J Luengo, S Garcıa, F Herrera. 2011
Soft Computing Techniques in Data Mining. J Alcalá-Fdez, F Herrera, H Ishibuchi, Y Kaisho, Y Nojima, BC Chien, .... 2011
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. 2010
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. 2010
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. 2010
Domains of competence of fuzzy rule based classification systems with data complexity measures: A case of study using a fuzzy hybrid genetic based machine learning method J Luengo, F Herrera. 2010
Geneticsbased machine learning for rule induction: Taxonomy, experimental study and state of the art A Fernández, S García, J Luengo, E Bernadó-Mansilla, F Herrera. 2010
A first study on the noise impact in classes for fuzzy rule based classification systems JA Sáez, J Luengo, F Herrera. 2010
An extraction method for the characterization of the Fuzzy Rule Based Classification Systems' behavior using data complexity measures: A case of study with FH-GBML J Luengo, F Herrera. 2010
Determinando Automáticamente los Dominios de Competencia de un Sistema de Clasificación Basado en Reglas Difusas: Un Caso de Estudio con FH-GBML J Luengo, F Herrera. 2010
Obtención de los dominios de competencia de C4. 5 por medio de medidas de separabilidad de clases J Luengo, F Herrera. 2010
Soft computing based learning and data analysis: missing values and data complexity J Luengo Martín. 2010
A study of statistical techniques and performance measures for genetics-based machine learning: accuracy and interpretability S García, A Fernández, J Luengo, F Herrera. 2009
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. 2009
A first approach to nearest hyperrectangle selection by evolutionary algorithms S García, J Derrac, J Luengo, F Herrera. 2009
Addressing data-complexity for imbalanced data-sets: A preliminary study on the use of preprocessing for c4. 5 J Luengo, A Fernández, S García, F Herrera. 2009
Implementation and integration of algorithms into the KEEL data-mining software tool A Fernández, J Luengo, J Derrac, J Alcalá-Fdez, F Herrera. 2009
On the use of Measures of Separability of Classes to Characterise the Domains of Competence of a Fuzzy Rule Based Classification System. J Luengo, F Herrera. 2009
Domains of competence of artificial neural networks using measures of separability of classes J Luengo, F Herrera. 2009
Social and educational exclusion as failures. Framework for their understanding and research M Jiménez, JJ Luengo, J Taberner. 2009
Competence-based approach in the development teacher training policy. Interview with Claude Lessard J Luengo, A Luzón, M Torres. 2008
A study on the use of statistical tests for experimentation with neural networks J Luengo, S García, F Herrera. 2007
Our experience in primary hyperaldosteronism S Gallego, A Covarsí, J Luengo, P González, MA Suarez, R Novillo. 2007
Nuestra experiencia en el hiperaldosteronismo primario S Gallego, A Covarsí, J Luengo, P González, MA Suarez, R Novillo. 2007
La educación como objeto de conocimiento. El concepto de educación J Luengo. 2004
La educación como hecho J Luengo. 2004
Revisión bibliográfica de disfunción craneomandibular del aņo 2000 O Rustullet Maņé, S Fradera, ÓJ Villalba Moreno, M Castellsagué, .... 2001
Disfunción craneomandibular. Revisión bibliográfica del aņo 1999 M Castellsagué, J Masdevall, O Rustullet Maņé, S Fradera, J Sabriā Rius, .... 2000
Disfunción craneomandibular. Revisión bibliográfica del año 1998 M Castellsagué, S Fradera, J Masdevall, J Pujol, O Rustullet, .... 1999
Disfunción craneomandibular. Revisión bibliográfica del año 1997 M Castellsagué, J Masdevall, A Revilla, JS Rius, S Fradera, J Pujol, .... 1998

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