Communication-Free Widened Learning of Bayesian Network Classifiers Using Hashed Fiedler Vectors

Sampson, Oliver R.; Borgelt, Christian; Berthold, Michael R.

Communication-Free Widened Learning of Bayesian Network Classifiers Using Hashed Fiedler Vectors

Dateien

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Datum

2018

Open Access-Veröffentlichung

Open Access Green

Sammlungen

Informatik und Informationswissenschaft

Publikationstyp

Beitrag zu einem Konferenzband

Publikationsstatus

Published

Erschienen in

DUIVESTEIJN, Wouter, ed., Arno SIEBES, ed., Antti UKKONEN, ed.. Advances in Intelligent Data Analysis XVII : 17th International Symposium, IDA 2018, ’s-Hertogenbosch, The Netherlands, October 24-26, 2018, proceedings. Cham: Springer, 2018, pp. 264-277. Lecture Notes in Computer Science. 11191. ISSN 0302-9743. eISSN 1611-3349. ISBN 978-3-030-01767-5. Available under: doi: 10.1007/978-3-030-01768-2_22

Zusammenfassung

Widening is a method where parallel resources are used to find better solutions from algorithms instead of merely trying to find the same solutions more quickly. To date, every example of Widening has used some from of communiucation between the parallel workers to maintain their distances from one another in the model space. For the first time, we present a communication-free, widened extension to a standard machine learning algorithm. By using Locality Sensitive Hashing on the Bayesian networks' Fiedler vectors, we demonstrate the ability to learn classifiers superior to those standard implementations and to those generated with a greedy heuristic alone

Fachgebiet (DDC)

004 Informatik

Konferenz

17th International Symposium, IDA 2018, 24. Okt. 2018 - 26. Okt. 2018, ’s-Hertogenbosch, The Netherlands

Zitieren

ISO 690

SAMPSON, Oliver R., Christian BORGELT, Michael R. BERTHOLD, 2018. Communication-Free Widened Learning of Bayesian Network Classifiers Using Hashed Fiedler Vectors. 17th International Symposium, IDA 2018. ’s-Hertogenbosch, The Netherlands, 24. Okt. 2018 - 26. Okt. 2018. In: DUIVESTEIJN, Wouter, ed., Arno SIEBES, ed., Antti UKKONEN, ed.. Advances in Intelligent Data Analysis XVII : 17th International Symposium, IDA 2018, ’s-Hertogenbosch, The Netherlands, October 24-26, 2018, proceedings. Cham: Springer, 2018, pp. 264-277. Lecture Notes in Computer Science. 11191. ISSN 0302-9743. eISSN 1611-3349. ISBN 978-3-030-01767-5. Available under: doi: 10.1007/978-3-030-01768-2_22

BibTex

@inproceedings{Sampson2018-10-05Commu-44696,
  year={2018},
  doi={10.1007/978-3-030-01768-2_22},
  title={Communication-Free Widened Learning of Bayesian Network Classifiers Using Hashed Fiedler Vectors},
  number={11191},
  isbn={978-3-030-01767-5},
  issn={0302-9743},
  publisher={Springer},
  address={Cham},
  series={Lecture Notes in Computer Science},
  booktitle={Advances in Intelligent Data Analysis XVII : 17th International Symposium, IDA 2018, ’s-Hertogenbosch, The Netherlands, October 24-26, 2018, proceedings},
  pages={264--277},
  editor={Duivesteijn, Wouter and Siebes, Arno and Ukkonen, Antti},
  author={Sampson, Oliver R. and Borgelt, Christian and Berthold, Michael R.}
}

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