86 citations · 347 across the 13 of their papers we have counts for
13 papers
A Unified Approach to Extract Interpretable Rules from Tree Ensembles via Integer Programming
Lorenzo Bonasera, Emilio Carrizosa
Tree ensembles are very popular machine learning models, known for their effectiveness in supervised classification and regression tasks. Their performance derives from aggregating…
Analysis of an aggregate loss model in a Markov renewal regime
Pepa Ramírez-Cobo, Emilio Carrizosa, Rosa Elvira Lillo
In this article we consider an aggregate loss model with dependent losses. The losses occurrence process is governed by a two-state Markovian arrival process (MAP2), a Markov renew…
Variable selection for Naïve Bayes classification
Rafael Blanquero, Emilio Carrizosa, Pepa Ramírez-Cobo +1
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 Na…
A cost-sensitive constrained Lasso
Rafael Blanquero, Emilio Carrizosa, Pepa Ramírez-Cobo +1
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 pre…
Cost-sensitive Feature Selection for Support Vector Machines
Sandra Benítez-Peña, Rafael Blanquero, Emilio Carrizosa +1
Feature Selection is a crucial procedure in Data Science tasks such as Classification, since it identifies the relevant variables, making thus the classification procedures more in…
On support vector machines under a multiple-cost scenario
Sandra Benítez-Peña, Rafael Blanquero, Emilio Carrizosa +1
Support Vector Machine (SVM) is a powerful tool in binary classification, known to attain excellent misclassification rates. On the other hand, many realworld classification proble…