Comparative Study of using Data Mining Techniques for Bank Telemarketing Data
Doha Hassan, Ali Rodan, Maher Salem, Moayyad Mohammad · 2019
In this paper, a heuristic and comparative study is performed to assess several data mining techniques using the well-known Bank Marking data set. We discuss how data mining (DM) techniques can be utilized to achieve result that is more accurate. All selected DM methods have been evaluated using bank telemarketing for clients from direct marketing campaigns (phone calls) of a Portuguese banking institution. The Bank marking data set has been created using 16 extracted features. Selected DM techniques are: neural network (NN), support vector machine (SVM), decision trees (DTs), k-nearest neighbour (KNN), naive Bayes (NB) and logistic regression (LR). The experiments show that the LR is capable of providing best performance with the true positive rate reaching 90.20%.