Predicting the Success of Bank Marketing System using Classification Techniques

Lukka Geetha,Kusam Anusha,Desham GaneshGoud,Sk. Mohammed Gouse,Venkata Naresh Mandhala

Marketing plays prominent role in any business field. It is very important in any field to promote its product to gain profit. This marketing or campaigning can be done in two ways one is direct interaction and other is through telecommunication that means communicating or interacting with the people through messages, emails or any other social media approach. For a person who is campaigning a product it is very important to know the reach of the product so that he could do any modifications that are needed, in his way of approach for promoting a product. In this project we are considering banking system, we are considering the data and going to find the persons who have subscribed for a scheme through different data mining techniques. By finding the number of persons subscribed to the scheme we can know up to what extent that scheme has reached to the people [1]. So if the bank system was not happy with the subscriptions they change the way of promoting. In our project we are comparing the predictions using different data mining techniques like Decision tree(DT),Naïve Bayes, Neural Networks(NN), KNN and support vector machine(SVM).Then we find the techniques that gives us the highest accuracy of prediction.

Volume 12 | Issue 2

Pages: 1961-1968

DOI: 10.5373/JARDCS/V12I2/S20201241