José A. Sáez

SMOTE–IPF: Addressing the noisy and borderline examples problem in imbalanced classification by a re-sampling method with filtering

José A. Sáez, Julián Luengo, Jerzy Stefanowski et al. · Information Sciences · 2014 · 597 citations

Data Classification, Classification Method, Engineering +12

A Survey of Discretization Techniques: Taxonomy and Empirical Analysis in Supervised Learning

Salvador García, Julián Luengo, José A. Sáez et al. · IEEE Transactions on Knowledge and Data Engineering · 2012 · 533 citations

Engineering, Machine Learning, Symbolic Data Analysis +25

Study on the Impact of Partition-Induced Dataset Shift on <formula formulatype="inline"><tex Notation="TeX">$k$</tex></formula>-Fold Cross-Validation

Jose G. Moreno-Torres, José A. Sáez, Francisco Herrera · IEEE Transactions on Neural Networks and Learning Systems · 2012 · 298 citations

Partition-induced Dataset Shift, Data Classification, Classification Method +14

Analyzing the oversampling of different classes and types of examples in multi-class imbalanced datasets

José A. Sáez, Bartosz Krawczyk, Michał Woźniak · Pattern Recognition · 2016 · 235 citations

Data Classification, Classification Method, Engineering +7

Analyzing the presence of noise in multi-class problems: alleviating its influence with the One-vs-One decomposition

José A. Sáez, Mikel Galar, Julián Luengo et al. · Knowledge and Information Systems · 2012 · 143 citations

Mathematical Programming, Computational Complexity Theory, Engineering +9