EXPLORE: A Novel Decision Tree Classification Algorithm

Md Zahidul Islam

doi:10.1007/978-3-642-25704-9_7

EXPLORE: A Novel Decision Tree Classification Algorithm

Research output: Book chapter/Published conference paper › Conference paper › peer-review

Abstract

Decision tree algorithms such as See5 (or C5) are typically used in data mining for classification and prediction purposes. In this study we propose EXPLORE, a novel decision tree algorithm, which is a modification of See5. The modifications are made to improve the capability of a tree in extracting hidden patterns. Justification of the proposed modifications is also presented. We experimentally compare EXPLORE with some existing algorithms such as See5, REPTree and J48 on several issues including quality of extracted rules/patterns, simplicity, and classification accuracy of the trees. Our initial experimental results indicate advantages of EXPLORE over existing algorithms.

Original language	English
Title of host publication	Data Security and Security Data
Subtitle of host publication	Proceedings of the 27th British National Conference on Databases (BNCOD 27)
Editors	Lachlan M. Mackinnon
Place of Publication	Germany
Publisher	Springer
Pages	55-71
Number of pages	17
Volume	6121
ISBN (Electronic)	9783642257049
ISBN (Print)	9783642257032
DOIs	https://doi.org/10.1007/978-3-642-25704-9_7
Publication status	Published - 2012
Event	27th British National Conference on Databases: BNCOD 27 - Dundee, UK, Dundee, United Kingdom Duration: 29 Jun 2010 → 01 Jul 2010 http://www.wikicfp.com/cfp/servlet/event.showcfp?eventid=7346&copyownerid=2

Publication series

Name
ISSN (Print)	0302-9743

Conference

Conference	27th British National Conference on Databases
Abbreviated title	Data Security and Security Data
Country/Territory	United Kingdom
City	Dundee
Period	29/06/10 → 01/07/10
Internet address	http://www.wikicfp.com/cfp/servlet/event.showcfp?eventid=7346&copyownerid=2

Access to Document

10.1007/978-3-642-25704-9_7

Cite this

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title = "EXPLORE: A Novel Decision Tree Classification Algorithm",

abstract = "Decision tree algorithms such as See5 (or C5) are typically used in data mining for classification and prediction purposes. In this study we propose EXPLORE, a novel decision tree algorithm, which is a modification of See5. The modifications are made to improve the capability of a tree in extracting hidden patterns. Justification of the proposed modifications is also presented. We experimentally compare EXPLORE with some existing algorithms such as See5, REPTree and J48 on several issues including quality of extracted rules/patterns, simplicity, and classification accuracy of the trees. Our initial experimental results indicate advantages of EXPLORE over existing algorithms.",

keywords = "Classification Algorithm, Data Mining, Decision Tree",

author = "Islam, {Md Zahidul}",

year = "2012",

doi = "10.1007/978-3-642-25704-9_7",

language = "English",

isbn = "9783642257032",

volume = "6121",

publisher = "Springer",

pages = "55--71",

editor = "Mackinnon, {Lachlan M.}",

booktitle = "Data Security and Security Data",

address = "United States",

note = "27th British National Conference on Databases : BNCOD 27, Data Security and Security Data ; Conference date: 29-06-2010 Through 01-07-2010",

url = "http://www.wikicfp.com/cfp/servlet/event.showcfp?eventid=7346&copyownerid=2",

}

Islam, MZ 2012, EXPLORE: A Novel Decision Tree Classification Algorithm. in LM Mackinnon (ed.), Data Security and Security Data: Proceedings of the 27th British National Conference on Databases (BNCOD 27). vol. 6121, Springer, Germany, pp. 55-71, 27th British National Conference on Databases, Dundee, United Kingdom, 29/06/10. https://doi.org/10.1007/978-3-642-25704-9_7

TY - GEN

T1 - EXPLORE: A Novel Decision Tree Classification Algorithm

AU - Islam, Md Zahidul

PY - 2012

Y1 - 2012

N2 - Decision tree algorithms such as See5 (or C5) are typically used in data mining for classification and prediction purposes. In this study we propose EXPLORE, a novel decision tree algorithm, which is a modification of See5. The modifications are made to improve the capability of a tree in extracting hidden patterns. Justification of the proposed modifications is also presented. We experimentally compare EXPLORE with some existing algorithms such as See5, REPTree and J48 on several issues including quality of extracted rules/patterns, simplicity, and classification accuracy of the trees. Our initial experimental results indicate advantages of EXPLORE over existing algorithms.

AB - Decision tree algorithms such as See5 (or C5) are typically used in data mining for classification and prediction purposes. In this study we propose EXPLORE, a novel decision tree algorithm, which is a modification of See5. The modifications are made to improve the capability of a tree in extracting hidden patterns. Justification of the proposed modifications is also presented. We experimentally compare EXPLORE with some existing algorithms such as See5, REPTree and J48 on several issues including quality of extracted rules/patterns, simplicity, and classification accuracy of the trees. Our initial experimental results indicate advantages of EXPLORE over existing algorithms.

KW - Classification Algorithm

KW - Data Mining

KW - Decision Tree

U2 - 10.1007/978-3-642-25704-9_7

DO - 10.1007/978-3-642-25704-9_7

M3 - Conference paper

SN - 9783642257032

VL - 6121

SP - 55

EP - 71

BT - Data Security and Security Data

A2 - Mackinnon, Lachlan M.

PB - Springer

CY - Germany

T2 - 27th British National Conference on Databases

Y2 - 29 June 2010 through 1 July 2010

ER -

EXPLORE: A Novel Decision Tree Classification Algorithm

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