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Energy modeling of ...
Energy modeling of Hoeffding tree ensembles
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- García Martín, Eva (författare)
- Blekinge Tekniska Högskola,Institutionen för datavetenskap
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- Bifet, A. (författare)
- Télécom ParisTech, Paris, France,Télécom ParisTech, FRA,Data, Intelligence and Graphs (DIG) LTCI
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- Lavesson, Niklas, Professor, 1976- (författare)
- Blekinge Tekniska Högskola,Jönköping University,Jönköping AI Lab (JAIL),Institutionen för datavetenskap,Jönköping University, SWE
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(creator_code:org_t)
- IOS Press, 2021
- 2021
- Engelska.
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Ingår i: Intelligent Data Analysis. - : IOS Press. - 1088-467X .- 1571-4128. ; 25:1, s. 81-104
- Relaterad länk:
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https://urn.kb.se/re...
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Abstract
Ämnesord
Stäng
- Energy consumption reduction has been an increasing trend in machine learning over the past few years due to its socio-ecological importance. In new challenging areas such as edge computing, energy consumption and predictive accuracy are key variables during algorithm design and implementation. State-of-the-art ensemble stream mining algorithms are able to create highly accurate predictions at a substantial energy cost. This paper introduces the nmin adaptation method to ensembles of Hoeffding tree algorithms, to further reduce their energy consumption without sacrificing accuracy. We also present extensive theoretical energy models of such algorithms, detailing their energy patterns and how nmin adaptation affects their energy consumption. We have evaluated the energy efficiency and accuracy of the nmin adaptation method on five different ensembles of Hoeffding trees under 11 publicly available datasets. The results show that we are able to reduce the energy consumption significantly, by 21% on average, affecting accuracy by less than one percent on average.
Ämnesord
- TEKNIK OCH TEKNOLOGIER -- Elektroteknik och elektronik -- Datorsystem (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Electrical Engineering, Electronic Engineering, Information Engineering -- Computer Systems (hsv//eng)
- NATURVETENSKAP -- Data- och informationsvetenskap -- Datavetenskap (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Computer Sciences (hsv//eng)
Nyckelord
- Data stream mining
- Energy efficiency
- Ensembles
- GreenAI
- Hoeffding trees
- Energy utilization
- Forestry
- Adaptation methods
- Algorithm design
- Energy patterns
- Predictive accuracy
- Socio-ecological
- State of the art
- Substantial energy
- Tree algorithms
- Green computing
Publikations- och innehållstyp
- ref (ämneskategori)
- art (ämneskategori)
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