Term deposit is always an essential business of a bank and a good market campaign plays an essential role in financial selling. Nowadays, the telephone marketing, which can assist consulting institution to extract potential clients, has been one of the most general marketing campaigns. Previous research shows that data mining has gradually stood out on the era of Big Data and has been incorporated to deal with massive data precisely. The purpose of this study is to predict the success of bank telemarketing to select the best consumer set. A relationship is observed between success and other factors through constructing logistic regression model. To validate the effectiveness of prediction, some basic classification models have been compared in this study, including Bayes, Support Vector Machine, Neural Network and Decision Tree. As a result, the prediction accuracy and the area under ROC curve prove the logistic regression model performs best in classifying than other models. All of the experiments are implemented by R language software. And the experimental results can provide some suggestions and instructions towards the management of the bank.
| Published in | International Journal on Data Science and Technology (Volume 4, Issue 1) |
| DOI | 10.11648/j.ijdst.20180401.15 |
| Page(s) | 35-41 |
| Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
| Copyright |
Copyright © The Author(s), 2018. Published by Science Publishing Group |
Term Deposit, Data Mining, Prediction, Logistic Regression Model, R Language
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APA Style
Yiyan Jiang. (2018). Using Logistic Regression Model to Predict the Success of Bank Telemarketing. International Journal on Data Science and Technology, 4(1), 35-41. https://doi.org/10.11648/j.ijdst.20180401.15
ACS Style
Yiyan Jiang. Using Logistic Regression Model to Predict the Success of Bank Telemarketing. Int. J. Data Sci. Technol. 2018, 4(1), 35-41. doi: 10.11648/j.ijdst.20180401.15
AMA Style
Yiyan Jiang. Using Logistic Regression Model to Predict the Success of Bank Telemarketing. Int J Data Sci Technol. 2018;4(1):35-41. doi: 10.11648/j.ijdst.20180401.15
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Download@article{10.11648/j.ijdst.20180401.15,
author = {Yiyan Jiang},
title = {Using Logistic Regression Model to Predict the Success of Bank Telemarketing},
journal = {International Journal on Data Science and Technology},
volume = {4},
number = {1},
pages = {35-41},
doi = {10.11648/j.ijdst.20180401.15},
url = {https://doi.org/10.11648/j.ijdst.20180401.15},
eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijdst.20180401.15},
abstract = {Term deposit is always an essential business of a bank and a good market campaign plays an essential role in financial selling. Nowadays, the telephone marketing, which can assist consulting institution to extract potential clients, has been one of the most general marketing campaigns. Previous research shows that data mining has gradually stood out on the era of Big Data and has been incorporated to deal with massive data precisely. The purpose of this study is to predict the success of bank telemarketing to select the best consumer set. A relationship is observed between success and other factors through constructing logistic regression model. To validate the effectiveness of prediction, some basic classification models have been compared in this study, including Bayes, Support Vector Machine, Neural Network and Decision Tree. As a result, the prediction accuracy and the area under ROC curve prove the logistic regression model performs best in classifying than other models. All of the experiments are implemented by R language software. And the experimental results can provide some suggestions and instructions towards the management of the bank.},
year = {2018}
}
TY - JOUR T1 - Using Logistic Regression Model to Predict the Success of Bank Telemarketing AU - Yiyan Jiang Y1 - 2018/06/21 PY - 2018 N1 - https://doi.org/10.11648/j.ijdst.20180401.15 DO - 10.11648/j.ijdst.20180401.15 T2 - International Journal on Data Science and Technology JF - International Journal on Data Science and Technology JO - International Journal on Data Science and Technology SP - 35 EP - 41 PB - Science Publishing Group SN - 2472-2235 UR - https://doi.org/10.11648/j.ijdst.20180401.15 AB - Term deposit is always an essential business of a bank and a good market campaign plays an essential role in financial selling. Nowadays, the telephone marketing, which can assist consulting institution to extract potential clients, has been one of the most general marketing campaigns. Previous research shows that data mining has gradually stood out on the era of Big Data and has been incorporated to deal with massive data precisely. The purpose of this study is to predict the success of bank telemarketing to select the best consumer set. A relationship is observed between success and other factors through constructing logistic regression model. To validate the effectiveness of prediction, some basic classification models have been compared in this study, including Bayes, Support Vector Machine, Neural Network and Decision Tree. As a result, the prediction accuracy and the area under ROC curve prove the logistic regression model performs best in classifying than other models. All of the experiments are implemented by R language software. And the experimental results can provide some suggestions and instructions towards the management of the bank. VL - 4 IS - 1 ER -
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