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Luengo García, David and Read, Jesse and Martino, Luca (2014). Efficient Monte Carlo methods for multi-dimensional learning with classifier chains. "Pattern Recognition", v. 47 (n. 3); pp. 1535-1546. ISSN 0031-3203. https://doi.org/10.1016/j.patcog.2013.10.006.
Title: | Efficient Monte Carlo methods for multi-dimensional learning with classifier chains |
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Author/s: |
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Item Type: | Article |
Título de Revista/Publicación: | Pattern Recognition |
Date: | March 2014 |
ISSN: | 0031-3203 |
Volume: | 47 |
Subjects: | |
Freetext Keywords: | Classifier chains; Multi-dimensional classification; Multi-label classification; Monte Carlo methods; Bayesian inference |
Faculty: | E.T.S.I. y Sistemas de Telecomunicación (UPM) |
Department: | Teoría de la Señal y Comunicaciones |
Creative Commons Licenses: | Recognition - No derivative works - Non commercial |
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Multi-dimensional classification (MDC) is the supervised learning problem where an instance is associated with multiple classes, rather than with a single class, as in traditional classification problems. Since these classes are often strongly correlated, modeling the dependencies between them allows MDC methods to improve their performance – at the expense of an increased computational cost. In this paper we focus on the classifier chains (CC) approach for modeling dependencies, one of the most popular and highest-performing methods for multi-label classification (MLC), a particular case of MDC which involves only binary classes (i.e., labels). The original CC algorithm makes a greedy approximation, and is fast but tends to propagate errors along the chain. Here we present novel Monte Carlo schemes, both for finding a good chain sequence and performing efficient inference. Our algorithms remain tractable for high-dimensional data sets and obtain the best predictive performance across several real data sets.
Type | Code | Acronym | Leader | Title |
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Government of Spain | CSD2008-00010 | COMONSENS | Unspecified | Unspecified |
Government of Spain | TEC2012-38800-C03-01 | ALCIT | Unspecified | Unspecified |
Government of Spain | TEC2012-38058-C03-01 | DISSECT | Unspecified | Unspecified |
Government of Spain | TEC2012-38883-C02-01 | COMPREHENSION | Unspecified | Unspecified |
Item ID: | 35934 |
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DC Identifier: | https://oa.upm.es/35934/ |
OAI Identifier: | oai:oa.upm.es:35934 |
DOI: | 10.1016/j.patcog.2013.10.006 |
Official URL: | http://www.sciencedirect.com/science/article/pii/S0031320313004160 |
Deposited by: | Memoria Investigacion |
Deposited on: | 12 Feb 2016 17:20 |
Last Modified: | 10 Jun 2019 06:56 |