Comparison of Classification Algorithms for Physical Activity Recognition
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F14%3A86096057" target="_blank" >RIV/61989100:27240/14:86096057 - isvavai.cz</a>
Alternative codes found
RIV/61989100:27740/14:86096057
Result on the web
<a href="http://dx.doi.org/10.1007/978-3-319-01781-5_12" target="_blank" >http://dx.doi.org/10.1007/978-3-319-01781-5_12</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-319-01781-5_12" target="_blank" >10.1007/978-3-319-01781-5_12</a>
Alternative languages
Result language
angličtina
Original language name
Comparison of Classification Algorithms for Physical Activity Recognition
Original language description
The main aim of this work is to compare different algorithms for human physical activity recognition from accelerometric and gyroscopic data which are recorded by a smartphone. Three classification algorithms were compared: the Linear Discriminant Analysis, the Random Forest, and the K-Nearest Neighbours. For better classification performance, two feature extraction methods were tested: the Correlation Subset Evaluation Method and the Principal Component Analysis. The results of experiment were expressed by confusion matrixes. (C) Springer International Publishing Switzerland 2014.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
IN - Informatics
OECD FORD branch
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Result continuities
Project
<a href="/en/project/EE.2.3.20.0073" target="_blank" >EE.2.3.20.0073: Bio-Inspired Methods: research, development and knowledge transfer</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach
Others
Publication year
2014
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Advances in Intelligent Systems and Computing. Volume 237
ISBN
978-3-319-01780-8
ISSN
2194-5357
e-ISSN
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Number of pages
9
Pages from-to
123-131
Publisher name
Springer
Place of publication
New York
Event location
Ostrava
Event date
Aug 22, 2013
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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