Modified balanced random forest for improving imbalanced data prediction

International Journal of Advances in Intelligent Informatics

View Publication Info
 
 
Field Value
 
Title Modified balanced random forest for improving imbalanced data prediction
 
Creator Agusta, Zahra Putri
Adiwijaya, Adiwijaya
 
Subject Imbalanced data; Random forest algorithm; Balanced random forest ; Customer churn; Classification technique
 
Description This paper proposes a Modified Balanced Random Forest (MBRF) algorithm as a classification technique to address imbalanced data. The MBRF process changes the process in a Balanced Random Forest by applying an under-sampling strategy based on clustering techniques for each data bootstrap decision tree in the Random Forest algorithm. To find the optimal performance of our proposed method compared with four clustering techniques, like: K-MEANS, Spectral Clustering, Agglomerative Clustering, and Ward Hierarchical Clustering. The experimental result show the Ward Hierarchical Clustering Technique achieved optimal performance, also the proposed MBRF method yielded better performance compared to the Balanced Random Forest (BRF) and Random Forest (RF) algorithms, with a sensitivity value or true positive rate (TPR) of 93.42%, a specificity or true negative rate (TNR) of 93.60%, and the best AUC accuracy value of 93.51%. Moreover, MBRF also reduced process running time.
 
Publisher Universitas Ahmad Dahlan
 
Contributor PT Telkom Indonesia, Graduated School Telkom University
 
Date 2019-03-31
 
Type info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion

 
Format application/pdf
 
Identifier http://ijain.org/index.php/IJAIN/article/view/255
10.26555/ijain.v5i1.255
 
Source International Journal of Advances in Intelligent Informatics; Vol 5, No 1 (2019): March 2019; 58-65
2548-3161
2442-6571
 
Language eng
 
Relation http://ijain.org/index.php/IJAIN/article/view/255/ijain_v5i1_p58-65
http://ijain.org/index.php/IJAIN/article/downloadSuppFile/255/56
 
Rights https://creativecommons.org/licenses/by-sa/4.0
 

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