original work is properly cited. Predicting Potential Banking Customer Churn using Apache Spark ML and MLlib Packages: A Comparative Study
Journal Title: International Journal of Advanced Computer Science & Applications - Year 2018, Vol 9, Issue 11
Abstract
This study was conducted based on an assumption that Spark ML package has much better performance and accuracy than Spark MLlib package in dealing with big data. The used dataset in the comparison is for bank customers transactions. The Decision tree algorithm was used with both packages to generate a model for predicting the churn proba-bility for bank customers depending on their transactions data. Detailed comparison results were recorded and conducted that the ML package and its new DataFrame-based APIs have better-evaluating performance and predicting accuracy.
Authors and Affiliations
Hend Sayed, Manal A. Abdel-Fattah, Sherif Kholief
Keywords
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- EP ID EP417778
- DOI 10.14569/IJACSA.2018.091196
- Views 78
- Downloads 0
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