Modified balanced random forest for improving imbalanced data prediction

Modified balanced random forest for improving imbalanced data prediction

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 tre...

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Bibliographic Details
Main Authors: Zahra Putri Agusta, Adiwijaya Adiwijaya
Format: Article
Language:English
Published: Universitas Ahmad Dahlan 2019-03-01
Series:IJAIN (International Journal of Advances in Intelligent Informatics)
Subjects:
Imbalanced data
Random forest algorithm
Balanced random forest
Customer churn
Classification technique
Online Access:http://ijain.org/index.php/IJAIN/article/view/255

Internet

http://ijain.org/index.php/IJAIN/article/view/255

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