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FPT University|e-Resources > Đồ án tốt nghiệp (Dissertations) > Kỹ thuật phần mềm (Software Engineering) >
Please use this identifier to cite or link to this item: /handle/123456789/1542

Authors: Jean, Daniel Zucker
Nhan, Huynh Van
An, Pham Ngoc
Keywords: Capstone Project
Đồ án tốt nghiệp
Data Mining applications
Prepaid churn model
Decision trees
Random Forest
Support Vector Machine
R language
Issue Date: 2015
Publisher: FPT University
Abstract: This paper evaluates different Machine Learning models which the aim to find out the good algorithm for predicting churners in prepaid telecom industry. Several models have been used and compared on the basis of different Data Mining methods and algorithm (Naïve Bayes, KNearest Neighbours, Decision Tree, Random Forest, and Support Vector Machine). To handle the imbalance in the data, we use Receiver Operating Characteristics (ROC) curves to evaluate the result beside the accuracy and churn rate. For the modeling examples we used RStudio analysis tool and introduced the R language.
URI: http://ds.libol.fpt.edu.vn/handle/123456789/1542
Appears in Collections:Kỹ thuật phần mềm (Software Engineering)

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