Online learning algorithm for ensemble of decision rules

Igor Chikalov; Mikhail Moshkov; Beata Zielosko

doi:10.1007/978-3-642-21881-1_48

Online learning algorithm for ensemble of decision rules

Igor Chikalov, Mikhail Moshkov, Beata Zielosko

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

6 Scopus citations

Abstract

We describe an online learning algorithm that builds a system of decision rules for a classification problem. Rules are constructed according to the minimum description length principle by a greedy algorithm or using the dynamic programming approach. © 2011 Springer-Verlag.

Original language	English (US)
Title of host publication	Rough Sets, Fuzzy Sets, Data Mining and Granular Computing
Publisher	Springer Nature
Pages	310-313
Number of pages	4
ISBN (Print)	9783642218804
DOIs	https://doi.org/10.1007/978-3-642-21881-1_48
State	Published - 2011

ASJC Scopus subject areas

Theoretical Computer Science
General Computer Science

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10.1007/978-3-642-21881-1_48

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@inproceedings{ced6cc1172354966966f4a137a7c2607,

title = "Online learning algorithm for ensemble of decision rules",

abstract = "We describe an online learning algorithm that builds a system of decision rules for a classification problem. Rules are constructed according to the minimum description length principle by a greedy algorithm or using the dynamic programming approach. {\textcopyright} 2011 Springer-Verlag.",

author = "Igor Chikalov and Mikhail Moshkov and Beata Zielosko",

note = "KAUST Repository Item: Exported on 2020-10-01",

year = "2011",

doi = "10.1007/978-3-642-21881-1_48",

language = "English (US)",

isbn = "9783642218804",

pages = "310--313",

booktitle = "Rough Sets, Fuzzy Sets, Data Mining and Granular Computing",

publisher = "Springer Nature",

}

TY - GEN

T1 - Online learning algorithm for ensemble of decision rules

AU - Chikalov, Igor

AU - Moshkov, Mikhail

AU - Zielosko, Beata

N1 - KAUST Repository Item: Exported on 2020-10-01

PY - 2011

Y1 - 2011

N2 - We describe an online learning algorithm that builds a system of decision rules for a classification problem. Rules are constructed according to the minimum description length principle by a greedy algorithm or using the dynamic programming approach. © 2011 Springer-Verlag.

AB - We describe an online learning algorithm that builds a system of decision rules for a classification problem. Rules are constructed according to the minimum description length principle by a greedy algorithm or using the dynamic programming approach. © 2011 Springer-Verlag.

UR - http://hdl.handle.net/10754/564339

UR - http://link.springer.com/10.1007/978-3-642-21881-1_48

UR - http://www.scopus.com/inward/record.url?scp=79960326399&partnerID=8YFLogxK

U2 - 10.1007/978-3-642-21881-1_48

DO - 10.1007/978-3-642-21881-1_48

M3 - Conference contribution

SN - 9783642218804

SP - 310

EP - 313

BT - Rough Sets, Fuzzy Sets, Data Mining and Granular Computing

PB - Springer Nature

ER -

Online learning algorithm for ensemble of decision rules

Abstract

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