Exploring nested ensemble learners using overproduction and choose approach for churn prediction in telecom industry
Abstract
Combining multiple classifiers to create hybrid learners (ensembles) has gained popularity in recent years. Ensembles are gaining more interest in the field of data mining as they have reportedly performed best predictions as compared to individual classifiers. This has resulted in experimentation with new ways of ensemble creation. This paper presents a study on creation of novel hybrid ways of combining multiple ensemble models using ‘over...
Paper Details
Title
Exploring nested ensemble learners using overproduction and choose approach for churn prediction in telecom industry
Published Date
Aug 18, 2018
Volume
32
Issue
8
Pages
3237 - 3251
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