86 citations · 235 across the 8 of their papers we have counts for
4 papers · 1 filter
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…
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…
Cost-sensitive probabilistic predictions for support vector machines
Sandra Benítez-Peña, Rafael Blanquero, Emilio Carrizosa +1
Support vector machines (SVMs) are widely used and constitute one of the best examined and used machine learning models for two-class classification. Classification in SVM is based…