Julián Luengo
Orcid: 0000-0003-3952-3629
According to our database1,
Julián Luengo
authored at least 90 papers
between 2007 and 2023.
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Bibliography
2023
Fusing anomaly detection with false positive mitigation methodology for predictive maintenance under multivariate time series.
Inf. Fusion, December, 2023
Multi-step histogram based outlier scores for unsupervised anomaly detection: ArcelorMittal engineering dataset case of study.
Neurocomputing, August, 2023
TSFEDL: A python library for time series spatio-temporal feature extraction and prediction using deep learning.
Neurocomputing, 2023
REVEL Framework to Measure Local Linear Explanations for Black-Box Models: Deep Learning Image Classification Case Study.
Int. J. Intell. Syst., 2023
Low-Impact Feature Reduction Regularization Term: How to Improve Artificial Intelligence with Explainability.
Proceedings of the Joint Proceedings of the xAI-2023 Late-breaking Work, 2023
Proceedings of the Hybrid Artificial Intelligent Systems - 18th International Conference, 2023
Proceedings of the Hybrid Artificial Intelligent Systems - 18th International Conference, 2023
2022
A tutorial on the segmentation of metallographic images: Taxonomy, new MetalDAM dataset, deep learning-based ensemble model, experimental analysis and challenges.
Inf. Fusion, 2022
Neurocomputing, 2022
The impact of heterogeneous distance functions on missing data imputation and classification performance.
Eng. Appl. Artif. Intell., 2022
TSFEDL: A Python Library for Time Series Spatio-Temporal Feature Extraction and Prediction using Deep Learning (with Appendices on Detailed Network Architectures and Experimental Cases of Study).
CoRR, 2022
2021
ME-MEOA/DCC: Multiobjective constrained clustering through decomposition-based memetic elitism.
Swarm Evol. Comput., 2021
Multiple instance classification: Bag noise filtering for negative instance noise cleaning.
Inf. Sci., 2021
Anomaly detection in predictive maintenance: A new evaluation framework for temporal unsupervised anomaly detection algorithms.
Neurocomputing, 2021
A robust approach for deep neural networks in presence of label noise: relabelling and filtering instances during training.
CoRR, 2021
Anomaly Detection in Predictive Maintenance: A New Evaluation Framework for Temporal Unsupervised Anomaly Detection Algorithms.
CoRR, 2021
Appl. Soft Comput., 2021
2020
COVIDGR Dataset and COVID-SDNet Methodology for Predicting COVID-19 Based on Chest X-Ray Images.
IEEE J. Biomed. Health Informatics, 2020
Fast and Scalable Approaches to Accelerate the Fuzzy k-Nearest Neighbors Classifier for Big Data.
IEEE Trans. Fuzzy Syst., 2020
Preprocessing methodology for time series: An industrial world application case study.
Inf. Sci., 2020
Comput. Oper. Res., 2020
Proceedings of the 53rd Hawaii International Conference on System Sciences, 2020
Proceedings of the Hybrid Artificial Intelligent Systems - 15th International Conference, 2020
Improving constrained clustering via decomposition-based multiobjective optimization with memetic elitism.
Proceedings of the GECCO '20: Genetic and Evolutionary Computation Conference, 2020
2019
Transforming big data into smart data: An insight on the use of the k-nearest neighbors algorithm to obtain quality data.
WIREs Data Mining Knowl. Discov., 2019
Coral species identification with texture or structure images using a two-level classifier based on Convolutional Neural Networks.
Knowl. Based Syst., 2019
Emerging topics and challenges of learning from noisy data in nonstandard classification: a survey beyond binary class noise.
Knowl. Inf. Syst., 2019
Neurocomputing, 2019
Neurocomputing, 2019
From Big to Smart Data: Iterative ensemble filter for noise filtering in Big Data classification.
Int. J. Intell. Syst., 2019
Towards highly accurate coral texture images classification using deep convolutional neural networks and data augmentation.
Expert Syst. Appl., 2019
Proceedings of the 4th International Conference on Internet of Things, 2019
Big Data Preprocessing as the Bridge between Big Data and Smart Data: BigDaPSpark and BigDaPFlink Libraries.
Proceedings of the 4th International Conference on Internet of Things, 2019
2018
Knowl. Based Syst., 2018
A First Study on the Use of Noise Filtering to Clean the Bags in Multi-Instance Classification.
Proceedings of the International Conference on Learning and Optimization Algorithms: Theory and Applications, 2018
A preliminary study on Hybrid Spill-Tree Fuzzy k-Nearest Neighbors for big data classification.
Proceedings of the 2018 IEEE International Conference on Fuzzy Systems, 2018
2017
Int. J. Comput. Intell. Syst., 2017
A Study on the Noise Label Influence in Boosting Algorithms: AdaBoost, GBM and XGBoost.
Proceedings of the Hybrid Artificial Intelligent Systems - 12th International Conference, 2017
Proceedings of the 2017 IEEE International Conference on Fuzzy Systems, 2017
2016
Soft Comput., 2016
Tutorial on practical tips of the most influential data preprocessing algorithms in data mining.
Knowl. Based Syst., 2016
INFFC: An iterative class noise filter based on the fusion of classifiers with noise sensitivity control.
Inf. Fusion, 2016
Evaluating the classifier behavior with noisy data considering performance and robustness: The Equalized Loss of Accuracy measure.
Neurocomputing, 2016
Proceedings of the 2016 IEEE International Conference on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, 2016
Proceedings of the Hybrid Artificial Intelligent Systems - 11th International Conference, 2016
2015
Intelligent Systems Reference Library 72, Springer, ISBN: 978-3-319-10247-4, 2015
Using the One-vs-One decomposition to improve the performance of class noise filters via an aggregation strategy in multi-class classification problems.
Knowl. Based Syst., 2015
An automatic extraction method of the domains of competence for learning classifiers using data complexity measures.
Knowl. Inf. Syst., 2015
SMOTE-IPF: Addressing the noisy and borderline examples problem in imbalanced classification by a re-sampling method with filtering.
Inf. Sci., 2015
A First Approach in the Class Noise Filtering Approaches for Fuzzy Subgroup Discovery.
Proceedings of the 10th International Conference on Soft Computing Models in Industrial and Environmental Applications, 2015
Naive Bayes Classifier with Mixtures of Polynomials.
Proceedings of the ICPRAM 2015, 2015
2014
Statistical computation of feature weighting schemes through data estimation for nearest neighbor classifiers.
Pattern Recognit., 2014
Analyzing the presence of noise in multi-class problems: alleviating its influence with the One-vs-One decomposition.
Knowl. Inf. Syst., 2014
On the characterization of noise filters for self-training semi-supervised in nearest neighbor classification.
Neurocomputing, 2014
Managing Borderline and Noisy Examples in Imbalanced Classification by Combining SMOTE with Ensemble Filtering.
Proceedings of the Intelligent Data Engineering and Automated Learning - IDEAL 2014, 2014
Improving the Behavior of the Nearest Neighbor Classifier against Noisy Data with Feature Weighting Schemes.
Proceedings of the Hybrid Artificial Intelligence Systems - 9th International Conference, 2014
2013
A Survey of Discretization Techniques: Taxonomy and Empirical Analysis in Supervised Learning.
IEEE Trans. Knowl. Data Eng., 2013
Predicting noise filtering efficacy with data complexity measures for nearest neighbor classification.
Pattern Recognit., 2013
Tackling the problem of classification with noisy data using Multiple Classifier Systems: Analysis of the performance and robustness.
Inf. Sci., 2013
An Experimental Case of Study on the Behavior of Multiple Classifier Systems with Class Noise Datasets.
Proceedings of the Hybrid Artificial Intelligent Systems - 8th International Conference, 2013
2012
Soft Comput., 2012
On the choice of the best imputation methods for missing values considering three groups of classification methods.
Knowl. Inf. Syst., 2012
Shared domains of competence of approximate learning models using measures of separability of classes.
Inf. Sci., 2012
An analysis on the use of pre-processing methods in evolutionary fuzzy systems for subgroup discovery.
Expert Syst. Appl., 2012
A Preliminary Study on Selecting the Optimal Cut Points in Discretization by Evolutionary Algorithms.
Proceedings of the ICPRAM 2012, 2012
A First Study on Decomposition Strategies with Data with Class Noise Using Decision Trees.
Proceedings of the Hybrid Artificial Intelligent Systems - 7th International Conference, 2012
A preliminary study on missing data imputation in evolutionary fuzzy systems of subgroup discovery.
Proceedings of the FUZZ-IEEE 2012, 2012
2011
Addressing data complexity for imbalanced data sets: analysis of SMOTE-based oversampling and evolutionary undersampling.
Soft Comput., 2011
KEEL Data-Mining Software Tool: Data Set Repository, Integration of Algorithms and Experimental Analysis Framework.
J. Multiple Valued Log. Soft Comput., 2011
Appl. Soft Comput., 2011
Fuzzy Rule Based Classification Systems versus crisp robust learners trained in presence of class noise's effects: A case of study.
Proceedings of the 11th International Conference on Intelligent Systems Design and Applications, 2011
2010
Genetics-Based Machine Learning for Rule Induction: State of the Art, Taxonomy, and Comparative Study.
IEEE Trans. Evol. Comput., 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 and EventCovering method.
Neural Networks, 2010
Advanced nonparametric tests for multiple comparisons in the design of experiments in computational intelligence and data mining: Experimental analysis of power.
Inf. Sci., 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.
Fuzzy Sets Syst., 2010
A first study on the noise impact in classes for Fuzzy Rule Based Classification Systems.
Proceedings of the 2010 IEEE International Conference on Intelligent Systems and Knowledge Engineering, 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.
Proceedings of the FUZZ-IEEE 2010, 2010
2009
A study of statistical techniques and performance measures for genetics-based machine learning: accuracy and interpretability.
Soft Comput., 2009
A study on the use of statistical tests for experimentation with neural networks: Analysis of parametric test conditions and non-parametric tests.
Expert Syst. Appl., 2009
Domains of Competence of Artificial Neural Networks Using Measures of Separability of Classes.
Proceedings of the Bio-Inspired Systems: Computational and Ambient Intelligence, 2009
Addressing Data-Complexity for Imbalanced Data-Sets: A Preliminary Study on the Use of Preprocessing for C4.5.
Proceedings of the Ninth International Conference on Intelligent Systems Design and Applications, 2009
Proceedings of the Ninth International Conference on Intelligent Systems Design and Applications, 2009
Implementation and Integration of Algorithms into the KEEL Data-Mining Software Tool.
Proceedings of the Intelligent Data Engineering and Automated Learning, 2009
On the use of Measures of Separability of Classes to Characterise the Domains of Competence of a Fuzzy Rule Based Classification System.
Proceedings of the Joint 2009 International Fuzzy Systems Association World Congress and 2009 European Society of Fuzzy Logic and Technology Conference, 2009
2007
Proceedings of the Computational and Ambient Intelligence, 2007