Oriental Journal of Computer Science and Technology

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Decision Tree Approach for Predicting Customers Credit Risk


Affiliations
1 Department of Computer Science & Systems Engineering, College of Engineering, Andhra University, Visakhapatnam - 530 003, India
2 Department of Computer Science, GITAM University, Visakhapatnam - 530 013, India
3 Sadineni Chowdaraiah College of Atrs and Science, Maddirala, Chilakaluripet - 522 611, India
 

This paper aims at constructing the customer data warehouse which adopts an improved ID3 decision tree algorithm to implement data mining in order to predict the risk class of the customer. The obtained results are compared with experimental results in order to verify the validity and accuracy of the developed model.

Keywords

Decision Tree, ID3, Classification, Association Rules.
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  • Decision Tree Approach for Predicting Customers Credit Risk

Abstract Views: 252  |  PDF Views: 3

Authors

K. Venkat Rao
Department of Computer Science & Systems Engineering, College of Engineering, Andhra University, Visakhapatnam - 530 003, India
T. Jyothirmayi
Department of Computer Science, GITAM University, Visakhapatnam - 530 013, India
M. V. Basaveswara Rao
Sadineni Chowdaraiah College of Atrs and Science, Maddirala, Chilakaluripet - 522 611, India

Abstract


This paper aims at constructing the customer data warehouse which adopts an improved ID3 decision tree algorithm to implement data mining in order to predict the risk class of the customer. The obtained results are compared with experimental results in order to verify the validity and accuracy of the developed model.

Keywords


Decision Tree, ID3, Classification, Association Rules.