Hybrid Gaussian and von Mises model-based clustering

Luengo Sánchez, Sergio ORCID: https://orcid.org/0000-0001-8537-1879, Larrañaga Múgica, Pedro María ORCID: https://orcid.org/0000-0002-1885-4501 and Bielza Lozoya, María Concepción ORCID: https://orcid.org/0000-0001-7109-2668 (2016). Hybrid Gaussian and von Mises model-based clustering. In: "European Conference on Artificial Intelligence, ECAI 2016", 29 Aug-02 Sep 2016, La Haya, Holanda. ISBN 978-1-61499-671-2. pp. 855-862. https://doi.org/10.3233/978-1-61499-672-9.

Description

Title: Hybrid Gaussian and von Mises model-based clustering
Author/s:
Item Type: Presentation at Congress or Conference (Article)
Event Title: European Conference on Artificial Intelligence, ECAI 2016
Event Dates: 29 Aug-02 Sep 2016
Event Location: La Haya, Holanda
Title of Book: Frontiers in Artificial Intelligence and Applications
Date: 2016
ISBN: 978-1-61499-671-2
Volume: 285
Subjects:
Faculty: E.T.S. de Ingenieros Informáticos (UPM)
Department: Inteligencia Artificial
Creative Commons Licenses: Recognition - No derivative works - Non commercial

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Abstract

Data collected about a phenomenon often measures its magnitude and direction. The most common approach to clustering this data assumes that directional data can be modeled as Gaussian. However, directional data has special properties that conventional statistics cannot handle. To deal with them, other approaches like the von Mises distribution must be applied. In this paper we present a new model based on mixtures of Bayesian networks to simultaneously cluster both linear and directional data.

Funding Projects

Type
Code
Acronym
Leader
Title
Government of Spain
C080020-09
Unspecified
Universidad Politécnica de Madrid
Cajal Blue Brain
Madrid Regional Government
S2013/ICE-284-5-CASI-CAM-CM
Unspecified
Unspecified
Unspecified
FP7
FP7/2007-2013
Unspecified
Unspecified
Human Brain Project

More information

Item ID: 46643
DC Identifier: https://oa.upm.es/46643/
OAI Identifier: oai:oa.upm.es:46643
DOI: 10.3233/978-1-61499-672-9
Official URL: http://ebooks.iospress.nl/volumearticle/44834
Deposited by: Memoria Investigacion
Deposited on: 15 Mar 2018 11:19
Last Modified: 30 Nov 2022 09:00
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