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Exploratory analysis of bank marketing campaign using machine learning; logistic regression, support vector machine and k-nearest neighbour

Oni, Jamiu Olalekan (2020) Exploratory analysis of bank marketing campaign using machine learning; logistic regression, support vector machine and k-nearest neighbour. Masters thesis, Dublin, National College of Ireland.

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Abstract

Bank marketing campaigns can be described as a technique or procedure designed by financial bodies particularly the banks to help reach the targeted needs or specifications of customers. This campaign could be said to be carried out or launched in various ways either using the internet, rally, social media, leaflet, emails, short message services, digital signage, blogging, strategic partnership, and other mediums. The endpoint of the campaign be it in any form is to meet the targeted needs of the customers thereby satisfying the customers. In this research work, the resampling technique was used to deal with the imbalance dataset and three classifiers were applied; Logistic regression, Support vector machine, and K-nearest neighbor were used to achieve the set objective. Comparative analysis was performed using correlation heatmap to identify the main factors that can increase customer subscriptions to a term deposit. The outcome shows that ‘Duration’ is the main factor that can increase customer subscriptions in the bank. two experiments were performed in this study. Of all the algorithms used in this work, KNN has the best performance with the accuracy of 91.8% in the first experiment and 91.7% in the second experiment as compared to the Support vector machine and Logistic regression.
Keywords: Correlation heatmap, K-nearest neighbor (KNN), Support vector machine (SVM), Logistic regression, Marketing campaign, Term deposit.

Item Type: Thesis (Masters)
Subjects: Q Science > QA Mathematics > Electronic computers. Computer science
T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science

Q Science > QA Mathematics > Computer software
T Technology > T Technology (General) > Information Technology > Computer software
Divisions: School of Computing > Master of Science in FinTech
Depositing User: Dan English
Date Deposited: 29 Jan 2021 17:13
Last Modified: 29 Jan 2021 17:13
URI: http://norma.ncirl.ie/id/eprint/4574

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