86 citations · 235 across the 8 of their papers we have counts for
5 papers · 1 filter
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 bivariate two-state Markov modulated Poisson process for failure modelling
Yoel G. Yera, Rosa E. Lillo, Bo F. Nielsen +2
Motivated by a real failure dataset in a two-dimensional context, this paper presents an extension of the Markov modulated Poisson process (MMPP) to two dimensions. The one-dimensi…
Fitting procedure for the two-state Batch Markov modulated Poisson process
Yoel G. Yera, Rosa E. Lillo, Pepa Ramírez-Cobo
The Batch Markov Modulated Poisson Process (BMMPP) is a subclass of the versatile Batch Markovian Arrival process (BMAP) which has been proposed for the modeling of dependent event…
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…