José A. Sáez
Orcid: 0000-0002-4592-1538
According to our database1,
José A. Sáez
authored at least 31 papers
between 2010 and 2024.
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Bibliography
2024
Tackling the problem of noisy IoT sensor data in smart agriculture: Regression noise filters for enhanced evapotranspiration prediction.
Expert Syst. Appl., March, 2024
2022
Pattern Recognit., 2022
2021
On the suitability of stacking-based ensembles in smart agriculture for evapotranspiration prediction.
Appl. Soft Comput., 2021
On the Regressand Noise Problem: Model Robustness and Synergy With Regression-Adapted Noise Filters.
IEEE Access, 2021
2019
Addressing the Overlapping Data Problem in Classification Using the One-vs-One Decomposition Strategy.
IEEE Access, 2019
KSUFS: A Novel Unsupervised Feature Selection Method Based on Statistical Tests for Standard and Big Data Problems.
IEEE Access, 2019
A Meta-Learning Recommendation System for Characterizing Unsupervised Problems: On Using Quality Indices to Describe Data Conformations.
IEEE Access, 2019
Dataset Weighting via Intrinsic Data Characteristics for Pairwise Statistical Comparisons in Classification.
Proceedings of the Hybrid Artificial Intelligent Systems - 14th International Conference, 2019
2018
Multi-class Imbalanced Data Oversampling for Vertebral Column Pathologies Classification.
Proceedings of the Hybrid Artificial Intelligent Systems - 13th International Conference, 2018
2016
Analyzing the oversampling of different classes and types of examples in multi-class imbalanced datasets.
Pattern Recognit., 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
On the Influence of Class Noise in Medical Data Classification: Treatment Using Noise Filtering Methods.
Appl. Artif. Intell., 2016
Tackling label noise with multi-class decomposition using fuzzy one-class support vector machines.
Proceedings of the 2016 IEEE International Conference on Fuzzy Systems, 2016
2015
SRCS: Statistical Ranking Color Scheme for Visualizing Parameterized Multiple Pairwise Comparisons with R.
R J., 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
SMOTE-IPF: Addressing the noisy and borderline examples problem in imbalanced classification by a re-sampling method with filtering.
Inf. Sci., 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
IEEE Trans. Neural Networks Learn. Syst., 2012
Soft Comput., 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
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
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