A Novel Classifier Model Efficient Prediction of Success Rate in Bank Marketing

  • Rama.A, A.Gayathri, P.V.Pramila

Abstract

This paper aims to present a classifier model using data mining tool WEKA, Where WEKA is an opensource tool based on machine learning to perform various data mining task. In this work the banking data is analyzed using the data mining tools. The analysis task includes five sub tasks that are dataset preparation, dataset preprocessing, identifying and developing a classifier model, and evaluation of the models. This process is used to preserve the data mining analysis and to discover the better classify model by applying parameter variation technique. A better classifier model for analyzing the dataset which have binary output.

Published
2020-06-02
How to Cite
Rama.A, A.Gayathri, P.V.Pramila. (2020). A Novel Classifier Model Efficient Prediction of Success Rate in Bank Marketing. International Journal of Advanced Science and Technology, 29(9s), 6955 - 6961. Retrieved from https://sersc.org/journals/index.php/IJAST/article/view/20658