Constrained Naïve Bayes with application to unbalanced data classification
Rafael Blanquero, Emilio Carrizosa, Pepa Ramírez Cobo, M Remedios Sillero-Denamiel.
(2021), Central European Journal of Operations Research, DOI: 10.1007/s10100-021-00782-1; Published online: 2021-10-20.
Keywords: Probabilistic Classification, Constrained optimization, Parameter estimation, Efficiency measures, Naïve Bayes.
Variable selection for Naïve Bayes classification
Rafael Blanquero, Emilio Carrizosa, Pepa Ramírez Cobo, M Remedios Sillero-Denamiel.
(2021), Computers & Operations Research, DOI: 10.1016/j.cor.2021.105456; Published online: 2021-06-02.
Keywords: Clustering, Conditional Independence, Dependence measures, Heuristics, Probabilistic Classification, Cost-sensitive Classification.
On Clustering Categories of Categorical Predictors in Generalized Linear Models
Emilio Carrizosa, Marcela Galvis Restrepo, Dolores Romero Morales.(2021), Expert Systems with Applications, DOI: 10.1016/j.eswa.2021.115245; Published online: 2021-05-24.
Keywords: Statistical Learning, Interpretability, Greedy Randomized Adaptive Search Procedure, Proximity between categories.
On sparse ensemble methods: An application to short-term predictions of the evolution of COVID-19
Sandra Benítez-Peña, Emilio Carrizosa, Vanesa Guerrero., M Dolores Jiménez-Gamero, Belén Martín-Barragán, Cristina Molero-Río, Pepa Ramírez-Cobo, Dolores Romero Morales, M Remedios Sillero-Denamiel,
Keywords: Machine Learning, Ensemble Method, Mathematical Optimization, Selective Sparsity, COVID-19.
Mathematical optimization in classification and regression trees
Emilio Carrizosa, Cristina Molero-Río, Dolores Romero Morales.(2021), TOP, DOI: 10.1007/s11750-021-00594-1; Published online: 2021-03-17.
Keywords: Classification and regression trees, Tree ensembles, Mixed-integer linear optimization, Continuous nonlinear optimization, Sparsity, Explainability.
Optimal randomized classification trees
Rafael Blanquero, Emilio Carrizosa, Cristina Molero-Río, Dolores Romero Morales.(2021), Computers & Operations Research, DOI: 10.1016/j.cor.2021.105281; Published online: 2021-03-08.
Keywords: Classification and regression trees, Cost-sensitive classification, Nonlinear programming.
A cost-sensitive constrained Lasso
Rafael Blanquero, Emilio Carrizosa, Pepa Ramírez-Cobo, M. Remedios Sillero-Denamiel.(2020), Advances in Data Analysis and Classification, DOI: 10.1007/s11634-020-00389-5; Published online: 2020-03-12.
Keywords: Performance constraints, Cost-sensitive learning, Sparse solutions, Sample average approximation, Heterogeneity, Lasso.
Expert-driven trace clustering with instance-level constraints
Pieter De Koninck, Klaas Nelissen, Seppe vanden Broucke, Bart Baesens, Monique Snoeck, Jochen De Weerdt(2020), Advances in Data Analysis and Classification, DOI: 10.1007/s10115-021-01548-6; Published online: 2020-03-01.
Keywords: Trace clustering, Process mining, Semi-supervised learning, Constrained clustering.
Sparsity in Optimal Randomized Classification Trees
Rafael Blanquero, Emilio Carrizosa , Cristina Molero-Río, Dolores Romero Morales(2019), European Journal of Operational Research, Elsevier Ltd., DOI: 10.1016/j.ejor.2019.12.002; Published online: 2019-12-16
Keywords: Data mining, Optimal Classification Trees, Global and Local Sparsity, Nonlinear Programming.
Enhancing Interpretability in Factor Analysis by Means of Mathematical Optimization
Emilio Carrizosa, Vanesa Guerrero, Dolores Romero Morales & Albert Satorra (2019), Multivariate Behavioral Research, DOI: 10.1080/00273171.2019.1677208; Published online: 2019-10-30
Keywords: Exploratory factor analysis, interpretability, factor rotation, explanatory variables, mathematical optimization
Feature Selection in Data Envelopment Analysis: A Mathematical Optimization approach