Relationships Between Average Depth and Number of Nodes for Decision Trees

Igor Chikalov; Shahid Hussain; Mikhail Moshkov

doi:10.1007/978-3-642-37832-4_47

Relationships Between Average Depth and Number of Nodes for Decision Trees

Igor Chikalov, Shahid Hussain, Mikhail Moshkov

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

5 Scopus citations

Abstract

This paper presents a new tool for the study of relationships between total path length or average depth and number of nodes of decision trees. In addition to algorithm, the paper also presents the results of experiments with datasets from UCI ML Repository [1]. © Springer-Verlag Berlin Heidelberg 2014.

Original language	English (US)
Title of host publication	Advances in Intelligent Systems and Computing
Publisher	Springer Nature
Pages	519-529
Number of pages	11
ISBN (Print)	9783642378317
DOIs	https://doi.org/10.1007/978-3-642-37832-4_47
State	Published - Jul 24 2013

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KAUST Repository Item: Exported on 2020-10-01

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10.1007/978-3-642-37832-4_47

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title = "Relationships Between Average Depth and Number of Nodes for Decision Trees",

abstract = "This paper presents a new tool for the study of relationships between total path length or average depth and number of nodes of decision trees. In addition to algorithm, the paper also presents the results of experiments with datasets from UCI ML Repository [1]. {\textcopyright} Springer-Verlag Berlin Heidelberg 2014.",

author = "Igor Chikalov and Shahid Hussain and Mikhail Moshkov",

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AU - Chikalov, Igor

AU - Hussain, Shahid

AU - Moshkov, Mikhail

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

PY - 2013/7/24

Y1 - 2013/7/24

N2 - This paper presents a new tool for the study of relationships between total path length or average depth and number of nodes of decision trees. In addition to algorithm, the paper also presents the results of experiments with datasets from UCI ML Repository [1]. © Springer-Verlag Berlin Heidelberg 2014.

AB - This paper presents a new tool for the study of relationships between total path length or average depth and number of nodes of decision trees. In addition to algorithm, the paper also presents the results of experiments with datasets from UCI ML Repository [1]. © Springer-Verlag Berlin Heidelberg 2014.

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UR - http://link.springer.com/10.1007/978-3-642-37832-4_47

UR - http://www.scopus.com/inward/record.url?scp=84888417026&partnerID=8YFLogxK

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DO - 10.1007/978-3-642-37832-4_47

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SP - 519

EP - 529

BT - Advances in Intelligent Systems and Computing

PB - Springer Nature

ER -

Relationships Between Average Depth and Number of Nodes for Decision Trees

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