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BoostVHT: Boosting distributed streaming decision trees
KTH.
2017 (English)In: International Conference on Information and Knowledge Management, Proceedings, Association for Computing Machinery , 2017, p. 899-908Conference paper, Published paper (Refereed)
Abstract [en]

Online boosting improves the accuracy of classifiers for unbounded streams of data by chaining them into an ensemble. Due to its sequential nature, boosting has proven hard to parallelize, even more so in the online setting. This paper introduces BoostVHT, a technique to parallelize online boosting algorithms. Our proposal leverages a recently-developed model-parallel learning algorithm for streaming decision trees as a base learner. This design allows to neatly separate the model boosting from its training. As a result, BoostVHT provides a flexible learning framework which can employ any existing online boosting algorithm, while at the same time it can leverage the computing power of modern parallel and distributed cluster environments. We implement our technique on Apache SAMOA, an open-source platform for mining big data streams that can be run on several distributed execution engines, and demonstrate order of magnitude speedups compared to the state-of-the-art.

Place, publisher, year, edition, pages
Association for Computing Machinery , 2017. p. 899-908
Keywords [en]
Boosting, Decision trees, Distributed systems, Online learning, Big data, Cluster computing, Clustering algorithms, Data mining, Distributed computer systems, Forestry, Knowledge management, Online systems, Trees (mathematics), Distributed clusters, Distributed streaming, Flexible Learning, Open source platforms, Parallel learning algorithms, Learning algorithms
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:kth:diva-227056DOI: 10.1145/3132847.3132974ISI: 000440845300089Scopus ID: 2-s2.0-85037345394ISBN: 9781450349185 OAI: oai:DiVA.org:kth-227056DiVA, id: diva2:1203551
Conference
26th ACM International Conference on Information and Knowledge Management, CIKM 2017, 6 November 2017 through 10 November 2017
Note

QC 20180503

Available from: 2018-05-03 Created: 2018-05-03 Last updated: 2018-08-28Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf