@conference{Cruz2011isda,
author = "Manuel Cruz-Ram{\'i}rez and C{\'e}sar Herv{\'a}s-Mart{\'i}nez and Javier S{\'a}nchez-Monedero and Pedro Antonio Guti{\'e}rrez",
abstract = "There are many metrics available to measure the goodness of a classifier
when working with ordinal datasets. These measures are divided into
product-moment and association metrics. In this paper, the behavior of
several metrics is studied in different situations. In addition, two new
measures associated with an ordinal classifier are defined: the maximum and
the minimum mean absolute error of all the classes. From the results of
this comparison, a pair of metrics is selected (one associated to the
overall error and another one to the error of the class with lowest level
of classification) to guide the evolution of a multi-objective evolutionary
algorithm, obtaining good results in generalization on ordinal datasets.",
address = "Cordoba, Spain, Spain",
booktitle = "11th International Conference on Intelligent Systems Design andApplications (ISDA 2011)",
keywords = "Mean Absolute Error, Multi-Objective Evolutionary Algorithm, Ordinal Measures",
month = "nov",
pages = "1176-1181",
title = "{A} {P}reliminary {S}tudy of {O}rdinal {M}etrics to {G}uide a {M}ulti-{O}bjective {E}volutionary {A}lgorithm",
year = "2011",
}