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Artificial Intelligence Review

Erschienen in:

11.07.2020

Multi-dimensional Bayesian network classifiers: A survey

verfasst von: Santiago Gil-Begue, Concha Bielza, Pedro Larrañaga

Erschienen in: Artificial Intelligence Review | Ausgabe 1/2021

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Abstract

Multi-dimensional classification is a cutting-edge problem, in which the values of multiple class variables have to be simultaneously assigned to a given example. It is an extension of the well known multi-label subproblem, in which the class variables are all binary. In this article, we review and expand the set of performance evaluation measures suitable for assessing multi-dimensional classifiers. We focus on multi-dimensional Bayesian network classifiers, which directly cope with multi-dimensional classification and consider dependencies among class variables. A comprehensive survey of this state-of-the-art classification model is offered by covering aspects related to their learning and inference process complexities. We also describe algorithms for structural learning, provide real-world applications where they have been used, and compile a collection of related software.

Vorheriger Artikel Dual generalized Bonferroni mean operators based on 2-dimensional uncertain linguistic information and their applications in multi-attribute decision making

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This is a simplification taken from Read et al. (2013) to facilitate discussion of the problem complexity. Actually, we will see later that each class variable can take a different number of values.

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Note that we have modified the term \(r_s = \sum _{j=1}^{d} |\Omega _{C_j}|\) of Fernandes et al. (2013) by d in the denominator of the equation in order to correctly normalize the score to lie between 0 and 1.

The popular approach to handle concept drifts named ensemble learning consists of combining the predictions of a set of individual classifiers, the so-called ensemble, in order to predict new incoming examples. A comprehensive review of ensemble approaches for data stream analysis was conducted by Krawczyk et al. (2017).

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Titel: Multi-dimensional Bayesian network classifiers: A survey
verfasst von: Santiago Gil-Begue
Concha Bielza
Pedro Larrañaga
Publikationsdatum: 11.07.2020
Verlag: Springer Netherlands
Erschienen in: Artificial Intelligence Review / Ausgabe 1/2021
Print ISSN: 0269-2821
Elektronische ISSN: 1573-7462
DOI: https://doi.org/10.1007/s10462-020-09858-x

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