NDLI: Joint Analysis of Multiple Algorithms and Performance Measures

Content Provider	Springer Nature Link
Author	de Campos, Cassio P. Benavoli, Alessio
Copyright Year	2016
Abstract	There has been an increasing interest in the development of new methods using Pareto optimality to deal with multi-objective criteria (for example, accuracy and time complexity). Once one has developed an approach to a problem of interest, the problem is then how to compare it with the state of art. In machine learning, algorithms are typically evaluated by comparing their performance on different data sets by means of statistical tests. Standard tests used for this purpose are able to consider jointly neither performance measures nor multiple competitors at once. The aim of this paper is to resolve these issues by developing statistical procedures that are able to account for multiple competing measures at the same time and to compare multiple algorithms altogether. In particular, we develop two tests: a frequentist procedure based on the generalized likelihood ratio test and a Bayesian procedure based on a multinomial-Dirichlet conjugate model. We further extend them by discovering conditional independences among measures to reduce the number of parameters of such models, as usually the number of studied cases is very reduced in such comparisons. Data from a comparison among general purpose classifiers are used to show a practical application of our tests.
Starting Page	69
Ending Page	86
Page Count	18
File Format	PDF
ISSN	02883635
Journal	New Generation Computing
Volume Number	35
Issue Number	1
e-ISSN	18827055
Language	English
Publisher	Ohmsha
Publisher Date	2016-12-12
Publisher Place	Tokyo
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Artificial Intelligence (incl. Robotics) Computer Hardware Computer Systems Organization and Communication Networks Software Engineering/Programming and Operating Systems Computing Methodologies
Content Type	Text
Resource Type	Article
Subject	Theoretical Computer Science Computer Networks and Communications Software Hardware and Architecture

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