Influence of Type and Level of Noise on the Performance of an Adaptive Novelty Detector
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21220%2F17%3A00317623" target="_blank" >RIV/68407700:21220/17:00317623 - isvavai.cz</a>
Result on the web
<a href="https://www.computer.org/csdl/proceedings/icci*cc/2017/0771/00/08109776.pdf" target="_blank" >https://www.computer.org/csdl/proceedings/icci*cc/2017/0771/00/08109776.pdf</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/ICCI-CC.2017.8109776" target="_blank" >10.1109/ICCI-CC.2017.8109776</a>
Alternative languages
Result language
angličtina
Original language name
Influence of Type and Level of Noise on the Performance of an Adaptive Novelty Detector
Original language description
This paper investigates the influence of the signal to noise ratio (SNR) and the type of a noise on the performance of two adaptive novelty detection methods. The evaluated methods are Learning Entropy (LE) and Error and Learning Based Novelty Detection (ELBND). The methods are compared in empirical way in classification framework. A classification based only on the error of the adaptive model was used as a reference. The research in this field is important, because a noise is present in every measured data and can drastically influence the result of tasks like the novelty detection. Moreover, various types of noise can influence the novelty detection in different ways, therefore the optimal method of adaptive novelty detection can be hard to choose. This assumption is supported by experimental results in this study.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2017
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
2017 IEEE 16TH INTERNATIONAL CONFERENCE ON COGNITIVE INFORMATICS & COGNITIVE COMPUTING (ICCI*CC)
ISBN
9781538607701
ISSN
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e-ISSN
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Number of pages
5
Pages from-to
373-377
Publisher name
IEEE
Place of publication
New York
Event location
Oxford
Event date
Jul 26, 2017
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000426941300058