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Mostrando ítems 1-10 de 12
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 ...
Artículo
On Extreme Concentrations in Chemical Reaction Networks with Incomplete Measurements
(ACS, 2016-11-09)
A fundamental problem in the analysis of chemical reactions networks consists of identifying concentration values along time or in steady state which are coherent with the experimental concentration data available. When ...
Artículo
Cost-sensitive feature selection for support vector machines
(Elsevier, 2018-03)
Feature Selection (FS) is a crucial procedure in Data Science tasks such as Classification, since it identifies the relevant variables, making thus the classification procedures more interpretable and more effective by ...
Artículo
Functional-bandwidth kernel for Support Vector Machine with Functional Data_An alternating optimization algorithm
(ELSEVIER SCIENCE BV, 2018-11-24)
Functional Data Analysis (FDA) is devoted to the study of data which are functions. Support Vector Ma- chine (SVM) is a benchmark tool for classification, in particular, of functional data. SVM is frequently used with a ...
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
On minimax-regret Huff location models
(Elsevier, 2011-01)
We address the following single-facility location problem: a firm is entering into a market by locating one facility in a region of the plane. The demand captured from each user by the facility will be proportional to the ...
Tesis Doctoral
Classification and regression with functional data: a mathematical optimization approach.
(2019-02-15)
El objetivo de esta tesis doctoral es desarrollar nuevos métodos para la clasificación y regresión supervisada en el Análisis de Datos Funcionales. En particular, las herramientas de Optimización Matemática analizadas en ...
Artículo
A global optimization method for model selection in chemical reactions networks
(PERGAMON-ELSEVIER SCIENCE LTD, 2016-06-07)
Model inference is a challenging problem in the analysis of chemical reactions networks. In order to empirically test which, out of a catalogue of proposed kinetic models, is governing a network of chemical reactions, ...
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 ...
Artículo
Sparsity in optimal randomized classification trees
(ELSEVIER SCIENCE BV, 2019-12-16)
Decision trees are popular Classification and Regression tools and, when small-sized, easy to interpret. Traditionally, a greedy approach has been used to build the trees, yielding a very fast training process; however, ...