Random rules from data streams
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F13%3A00068420" target="_blank" >RIV/00216224:14330/13:00068420 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1145/2480362.2480518" target="_blank" >http://dx.doi.org/10.1145/2480362.2480518</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1145/2480362.2480518" target="_blank" >10.1145/2480362.2480518</a>
Alternative languages
Result language
angličtina
Original language name
Random rules from data streams
Original language description
Existing works suggest that random inputs and random features produce good results in classification. In this paper we study the problem of generating random rule sets from data streams. One of the most interpretable and flexible models for data stream mining prediction tasks is the Very Fast Decision Rules learner (VFDR). In this work we extend the VFDR algorithm using random rules from data streams. The proposed algorithm generates several sets of rules. Each rule set is associated with a set of Nattattributes. The proposed algorithm maintains all properties required when learning from stationary data streams: online and any-time classification, processing each example once.
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/LG13010" target="_blank" >LG13010: Czech Republic representation in the European Research Consortium for Informatics and Mathematics (ERCIM)</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2013
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings of the 28th Annual ACM Symposium on Applied Computing, SAC '13
ISBN
9781450316569
ISSN
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e-ISSN
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Number of pages
2
Pages from-to
813-814
Publisher name
ACM
Place of publication
New York, NY, USA
Event location
Coimbra, Portugal
Event date
Jan 1, 2013
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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