Analog the performance between three classifiers on bank marketing data

Abstract

There are several different classification methods can be used to do the classification which can classified the data into specified groups or classes. This paper presents a comparison of performance between three classifiers which include Naïve Bayes, Decision Tree and Neural Network on Bank Marketing dataset. This study focus on which classifier will have the better performance based on some performance measure in two different datasets. The result shows that machine learning classifier was not able compare to Naïve Bayes and Decision Tree classifier. Based on the results, the huge dataset obtained the more information which can be predict accurately and identify the performance of the classifier correctly.