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Mostrando ítems 1-10 de 11
Artículo
On sparse optimal regression trees
(Elsevier, 2021-12-18)
In this paper, we model an optimal regression tree through a continuous optimization problem, where a compromise between prediction accuracy and both types of sparsity, namely local and global, is sought. Our approach can ...
Tesis Doctoral
New models and methods for classification and feature selection. a mathematical optimization perspective
(2021-07-27)
The objective of this PhD dissertation is the development of new models for Supervised Classification and Benchmarking, making use of Mathematical Optimization and Statistical tools. Particularly, we address the fusion ...
Tesis Doctoral
Enhancing Classification and Regression Tree-Based Models by means of Mathematical Optimization
(2022-12-19)
This PhD dissertation bridges the disciplines of Operations Research and Machine Learning by developing novel Mathematical Optimization formulations and numerical solution approaches to build classification and regression ...
Artículo
Re-identification of fish individuals of undulate skate via deep learning within a few-shot context
(ScienceDirect, 2023-02-28)
Individual re-identification is critical to track population changes in order to assess status, being particularly relevant in species with conservation concerns and difficult access like marine organisms. For this, we ...
Tesis Doctoral
Computational Methods for the Analysis of Complex Data
(2021-07-07)
This PhD dissertation bridges the disciplines of Operations Research and Statistics to develop novel computational methods for the extraction of knowledge from complex data. In this research, complex data stands for ...
Artículo
Selection of time instants and intervals with Support Vector Regression for multivariate functional data
(PERGAMON-ELSEVIER SCIENCE LTD, 2020-07-19)
When continuously monitoring processes over time, data is collected along a whole period, from which only certain time instants and certain time intervals may play a crucial role in the data analysis. We develop a method ...
Artículo
Constrained Naïve Bayes with application to unbalanced data classification
(Springer, 2021-09-15)
The Naïve Bayes is a tractable and efficient approach for statistical classification. In general classification problems, the consequences of misclassifications may be rather different in different classes, making it ...
Artículo
Variable selection for Naïve Bayes classification
(Pergamon-Elsevier Science Ltd., 2021-07-06)
The Naïve Bayes has proven to be a tractable and efficient method for classification in multivariate analysis. However, features are usually correlated, a fact that violates the Naïve Bayes’ assumption of conditional ...
Artículo
Variable selection for Naïve Bayes classification
(Elsevier, 2021)
The Naïve Bayes has proven to be a tractable and efficient method for classification in multivariate analysis. However, features are usually correlated, a fact that violates the Naïve Bayes’ assumption of conditional i ...
Artículo
A cost-sensitive constrained Lasso
(Springer, 2020-03-02)
The Lasso has become a benchmark data analysis procedure, and numerous variants have been proposed in the literature. Although the Lasso formulations are stated so that overall prediction error is optimized, no full ...