Analysis of error rate for various attributes to obtain the optimal decision tree

Title

Analysis of error rate for various attributes to obtain the optimal decision tree

Creator

Mahesawri K.; Ramkumar S.

Description

The competitiveness and computational intelligence are required to increase the gross profit of the product in a market. The classification algorithm rpart is applied on retail market dataset. The regression rpart decision tree algorithm is implemented with principal component analysis to impute data in the missing part of the dataset. The objective is to obtain an optimal tree by analysing cross validation error, standard deviation error, and number of splits and relative error of various attributes. The results of various attributes by ANOVA method are compared to choose the best optimal tree. The tree with minimum error rate is considered for the optimal tree. Copyright 2022 Inderscience Enterprises Ltd.

Source

International Journal of Intelligent Enterprise, Vol-9, No. 4, pp. 458-472.

Date

2022-01-01

Publisher

Inderscience Publishers

Subject

data mining; decision tree; error rate; pruning

Coverage

Mahesawri K., Department of Computer Applications, School of Computing, Kalasalingam Academy of Research and Education, Virudhunagar (DT), Krishnankoil, India; Ramkumar S., Department of Business Analytics, School of Business and Management, Christ University, Bengaluru, 560-029, India

Rights

Restricted Access

Relation

ISSN: 17453232

Format

Online

Language

English

Type

Conference paper

Identifier

https://doi.org/10.1504/ijie.2022.126400

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85142765952&doi=10.1504%2fijie.2022.126400&partnerID=40&md5=5bf069263aa5b60fb5c58f489508354b