Discovering Relevant Sensor Data by Q-Analysis

Research output: Chapter in Book/Report/Conference proceedingChapter

1 Citation (Scopus)

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.
Original 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
Publication statusPublished - 2005

Publication series

NameLecture Notes in Computer Science
PublisherSpringer

Fingerprint Dive into the research topics of 'Discovering Relevant Sensor Data by Q-Analysis'. Together they form a unique fingerprint.

Cite this