José A. Sáez

33 papers B 1C 2Misc 5Journal 23Unranked 2
YearRankTypeTitle / Venue / Authors
2025 J jnl
A Survey of Preprocessing Techniques for Flow Cytometry Data in Classification Tasks.
IEEE Trans. Comput. Biol. Bioinform.
David Núñez-Nepomuceno, José A. Sáez, Pedro Carmona-Saez
2025 — conf
When Colorimetry Meets the Cloud: IoT-Enabled Health Monitoring at Home via Highly-Specific Gas Sensing.
AINA (3)
Ismael Benito-Altamirano, Omar Romera-Aller, Miquel Alfaras, Zouhair Haddi, Anaïs Espinoso, Xavier Llauradó, José A. Sáez, Cristian Fàbrega Gallego
2024 J jnl
Compact Class-Conditional Attribute Category Clustering: Amino Acid Grouping for Enhanced HIV-1 Protease Cleavage Classification.
IEEE ACM Trans. Comput. Biol. Bioinform.
José A. Sáez, José Fernando Vera
2024 J jnl
Tackling the problem of noisy IoT sensor data in smart agriculture: Regression noise filters for enhanced evapotranspiration prediction.
Expert Syst. Appl.
Juan Martín, José A. Sáez, Emilio Corchado
2022 J jnl
ANCES: A novel method to repair attribute noise in classification problems.
Pattern Recognit.
José A. Sáez, Emilio Corchado
2021 J jnl
On the Regressand Noise Problem: Model Robustness and Synergy With Regression-Adapted Noise Filters.
IEEE Access
Juan Martín, José A. Sáez, Emilio Corchado
2021 J jnl
On the suitability of stacking-based ensembles in smart agriculture for evapotranspiration prediction.
Appl. Soft Comput.
Juan Martín, José A. Sáez, Emilio Corchado
2019 J jnl
A Meta-Learning Recommendation System for Characterizing Unsupervised Problems: On Using Quality Indices to Describe Data Conformations.
IEEE Access
José A. Sáez, Emilio Corchado
2019 J jnl
Addressing the Overlapping Data Problem in Classification Using the One-vs-One Decomposition Strategy.
IEEE Access
José A. Sáez, Mikel Galar, Bartosz Krawczyk
2019 Misc conf
Dataset Weighting via Intrinsic Data Characteristics for Pairwise Statistical Comparisons in Classification.
HAIS
José A. Sáez, Pablo J. Villacorta, Emilio Corchado
2019 J jnl
KSUFS: A Novel Unsupervised Feature Selection Method Based on Statistical Tests for Standard and Big Data Problems.
IEEE Access
José A. Sáez, Emilio Corchado
2018 Misc conf
Multi-class Imbalanced Data Oversampling for Vertebral Column Pathologies Classification.
HAIS
José A. Sáez, Héctor Quintián, Bartosz Krawczyk, Michal Wozniak, Emilio Corchado
2016 J jnl
Analyzing the oversampling of different classes and types of examples in multi-class imbalanced datasets.
Pattern Recognit.
José A. Sáez, Bartosz Krawczyk, Michal Wozniak
2016 J jnl
Evaluating the classifier behavior with noisy data considering performance and robustness: The Equalized Loss of Accuracy measure.
Neurocomputing
José A. Sáez, Julián Luengo, Francisco Herrera
2016 J jnl
INFFC: An iterative class noise filter based on the fusion of classifiers with noise sensitivity control.
Inf. Fusion
José A. Sáez, Mikel Galar, Julián Luengo, Francisco Herrera
2016 J jnl
On the Influence of Class Noise in Medical Data Classification: Treatment Using Noise Filtering Methods.
Appl. Artif. Intell.
José A. Sáez, Bartosz Krawczyk, Michal Wozniak
2016 B conf
Tackling label noise with multi-class decomposition using fuzzy one-class support vector machines.
FUZZ-IEEE
Bartosz Krawczyk, José A. Sáez, Michal Wozniak
2015 J jnl
SMOTE-IPF: Addressing the noisy and borderline examples problem in imbalanced classification by a re-sampling method with filtering.
Inf. Sci.
José A. Sáez, Julián Luengo, Jerzy Stefanowski, Francisco Herrera
2015 J jnl
SRCS: Statistical Ranking Color Scheme for Visualizing Parameterized Multiple Pairwise Comparisons with R.
R J.
Pablo J. Villacorta, José A. Sáez
2015 J jnl
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.
Luís Paulo F. Garcia, José A. Sáez, Julián Luengo, Ana Carolina Lorena, André C. P. L. F. de Carvalho, Francisco Herrera
2014 J jnl
Analyzing the presence of noise in multi-class problems: alleviating its influence with the One-vs-One decomposition.
Knowl. Inf. Syst.
José A. Sáez, Mikel Galar, Julián Luengo, Francisco Herrera
2014 Misc conf
Improving the Behavior of the Nearest Neighbor Classifier against Noisy Data with Feature Weighting Schemes.
HAIS
José A. Sáez, Joaquín Derrac, Julián Luengo, Francisco Herrera
2014 C conf
Managing Borderline and Noisy Examples in Imbalanced Classification by Combining SMOTE with Ensemble Filtering.
IDEAL
José A. Sáez, Julián Luengo, Jerzy Stefanowski, Francisco Herrera
2014 J jnl
On the characterization of noise filters for self-training semi-supervised in nearest neighbor classification.
Neurocomputing
Isaac Triguero, José A. Sáez, Julián Luengo, Salvador García, Francisco Herrera
2014 J jnl
Statistical computation of feature weighting schemes through data estimation for nearest neighbor classifiers.
Pattern Recognit.
José A. Sáez, Joaquín Derrac, Julián Luengo, Francisco Herrera
2013 Misc conf
An Experimental Case of Study on the Behavior of Multiple Classifier Systems with Class Noise Datasets.
HAIS
José A. Sáez, Mikel Galar, Julián Luengo, Francisco Herrera
2013 J jnl
Predicting noise filtering efficacy with data complexity measures for nearest neighbor classification.
Pattern Recognit.
José A. Sáez, Julián Luengo, Francisco Herrera
2013 J jnl
Tackling the problem of classification with noisy data using Multiple Classifier Systems: Analysis of the performance and robustness.
Inf. Sci.
José A. Sáez, Mikel Galar, Julián Luengo, Francisco Herrera
2012 — conf
A First Study on Decomposition Strategies with Data with Class Noise Using Decision Trees.
HAIS (2)
José A. Sáez, Mikel Galar, Julián Luengo, Francisco Herrera
2012 J jnl
Missing data imputation for fuzzy rule-based classification systems.
Soft Comput.
Julián Luengo, José A. Sáez, Francisco Herrera
2012 J jnl
Study on the Impact of Partition-Induced Dataset Shift on k -Fold Cross-Validation.
IEEE Trans. Neural Networks Learn. Syst.
Jose G. Moreno-Torres, José A. Sáez, Francisco Herrera
2011 C conf
Fuzzy Rule Based Classification Systems versus crisp robust learners trained in presence of class noise's effects: A case of study.
ISDA
José A. Sáez, Julián Luengo, Francisco Herrera
2010 Misc conf
A first study on the noise impact in classes for Fuzzy Rule Based Classification Systems.
ISKE
José A. Sáez, Julián Luengo, Francisco Herrera