Título Numerical variable reconstruction from ordinal categories based on probability distributions
Autores SÁNCHEZ MONEDERO, JAVIER, CARBONERO RUZ, MARIANO, BECERRA ALONSO, DAVID, MARTÍNEZ ESTUDILLO, FRANCISCO JOSÉ, Gutiérrez P.A. , Hervás-Martínez C.
Publicación externa No
Medio Int. Conf. Intell. Syst. Des. Appl., ISDA
Alcance Conference Paper
Naturaleza Científica
Web https://www.scopus.com/inward/record.uri?eid=2-s2.0-84857589580&doi=10.1109%2fISDA.2011.6121819&partnerID=40&md5=05b934c1dc76426f06b2f6db11f644ed
Fecha de publicacion 01/01/2011
Scopus Id 2-s2.0-84857589580
DOI 10.1109/ISDA.2011.6121819
Abstract Ordinal classification problems are an active research area in the machine learning community. Many previous works adapted state-of-art nominal classifiers to improve ordinal classification so that the method can take advantage of the ordinal structure of
Palabras clave Class labels; Data sets; Machine learning communities; Mathematical basis; Method improvement; Numerical variables; Ordinal classification; Ordinal regression; Ordinal structure; Regression model; Reg
Miembros de la Universidad Loyola

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