Discovering Relevant Sensor Data by Q-Analysis

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

This paper proposes a novel method for supervised classification based on the methodology of Q-analysis. The classification is based on finding `relevant' structures in the features describing the data, and using them to define each of the classes. The features not included in the structural definition of a class are considered as `irrelevant'. The paper uses three diferent data-sets to experimentally validate the method.
LanguageEnglish
Title of host publicationRoboCup 2005: Robot Soccer World Cup IX
Place of PublicationBerlin
PublisherSpringer
Pages81-92
Number of pages12
Volume4020/2006
ISBN (Print)978-3-540-35437-6
DOIs
StatusPublished - 2005

Publication series

NameLecture Notes in Computer Science
PublisherSpringer

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Sensors

Cite this

Iravani, P. (2005). Discovering Relevant Sensor Data by Q-Analysis. In RoboCup 2005: Robot Soccer World Cup IX (Vol. 4020/2006, pp. 81-92). (Lecture Notes in Computer Science). Berlin: Springer. https://doi.org/10.1007/11780519_8

Discovering Relevant Sensor Data by Q-Analysis. / Iravani, Pejman.

RoboCup 2005: Robot Soccer World Cup IX. Vol. 4020/2006 Berlin : Springer, 2005. p. 81-92 (Lecture Notes in Computer Science).

Research output: Chapter in Book/Report/Conference proceedingChapter

Iravani, P 2005, Discovering Relevant Sensor Data by Q-Analysis. in RoboCup 2005: Robot Soccer World Cup IX. vol. 4020/2006, Lecture Notes in Computer Science, Springer, Berlin, pp. 81-92. https://doi.org/10.1007/11780519_8
Iravani P. Discovering Relevant Sensor Data by Q-Analysis. In RoboCup 2005: Robot Soccer World Cup IX. Vol. 4020/2006. Berlin: Springer. 2005. p. 81-92. (Lecture Notes in Computer Science). https://doi.org/10.1007/11780519_8
Iravani, Pejman. / Discovering Relevant Sensor Data by Q-Analysis. RoboCup 2005: Robot Soccer World Cup IX. Vol. 4020/2006 Berlin : Springer, 2005. pp. 81-92 (Lecture Notes in Computer Science).
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