Customer Retention in Banking Sector using Decision Tree-Neuro Based System
Tamilmani.G1, Rajathi.K2
1Tamilmani.G*, Assistant Professor, Computer Science and Engineering, Vel tech Rangarajan Dr.Sagunthala R & D Institute of Technology, Avadi, Chennai.
2Rajathi.K, Associate Professor, Computer Science and Engineering, Vel tech Rangarajan Dr.Sagunthala R & D Institute of Technology, Avadi, Chennai.
Manuscript received on February 01, 2020. | Revised Manuscript received on February 05, 2020. | Manuscript published on February 30, 2020. | PP: 481-485 | Volume-9 Issue-3, February, 2020. | Retrieval Number: C4856029320/2020©BEIESP | DOI: 10.35940/ijeat.C4856.029320
Open Access | Ethics and Policies | Cite | Mendeley
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: All the bank marketing campaigns mostly deals with large amount of data. when they need to deal with huge electronic data of customers, then it is very difficult to analyze the data manually or by human analyst. Here comes the picture of data mining techniques to deal with the large amount of data and to come up with useful data which helps in decision making process. All the data mining techniques helps in analyzing the data. some of the techniques that can be used for this bank marketing campaigns are naive bayes, logistics regression technique and Decision tree model technique etc. among all these techniques decision Tree model gives the best solution in analyzing the human decisions. Artificial neural networks is a learning algorithm which learns from multiple individual decisions and their judgements, thus aggregates and generalizes the customers decision making knowledge.
Keywords: Decision Tree Model Technique, Artificial Neural Network, logistics regression.