A Theoretical Framework on the Ideal Number of Classifiers for Online Ensembles in Data Streams-Reference-Cited by-同舟云学术

A Theoretical Framework on the Ideal Number of Classifiers for Online Ensembles in Data Streams

Published:2016-10-24 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 25th ACM International on Conference on Information and Knowledge Management
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Author:

Bonab Hamed R.¹,Can Fazli¹

Affiliation:

1. Bilkent University, Ankara, Turkey

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/2983323.2983907

Reference14 articles.

1. X. Zhu Stream Data Mining Repository http://www.cse.fau.edu/ xqzhu/stream.html 2010. X. Zhu Stream Data Mining Repository http://www.cse.fau.edu/ xqzhu/stream.html 2010.

2. New ensemble methods for evolving data streams

3. Reacting to different types of concept drift: The accuracy updated ensemble algorithm;Brzezinski D.;IEEE TNNLS,2014

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