Predicting Bank Term Deposit Subscription using Machine Learning Algorithms

Running head: FOUNDATIONS OF DATA SCIENCE
Foundations of Data Science
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Foundations of Data Science2
Abstract
From the past analysis it has been observed that the Portuguese bank have seen a decline in the revenue,
thus the bank has decided to take required action accordingly. After different investigation and analysis the
reason behind the declination was observed to be that the clients were not depositing money to the bank as
frequently as they did before. Fixed deposit or term deposits helps any bank by investing in some other
marketing strategies so that the bank can gain profit by such steps. People opt for fixed deposits as the
deposit for a limited time period can give them a whole lot of money with interest for individual bank.
Thus the main purpose of the analysis is that the Portuguese bank want to identify if from the existing
customers who have the higher chances to subscribe for a term deposit and the bank would like to focus
marketing effort over such clients.
The data used in this analysis is totally related to a marketing campaign which was organized by the
Portuguese banking institution. The campaign was totally based on phone calls where the bank marketing
peoples arranged the campaign using phone calls. More than one contact were registered for the same client
in order to access the information weather the client will subscribe or not. In the dataset “y” attribute is the
target variable which says weather the customer subscribed to the term deposit or not.
Different analysis and visualization have been performed to understand the relationship with different
attributes and at the end data pre-processing and building model has been done using five different machine
learning models. The classification model with the highest accuracy will be taken for consideration.
At the end a conclusion will be concluded based on the analysis and the outcomes of each model to predict
the potential customer.

Foundations of Data Science3
Table of Contents
Abstract............................................................................................................................................................2
Introduction......................................................................................................................................................4
Data...................................................................................................................................................................4
Methods............................................................................................................................................................4
Data Representation...................................................................................................................................5
Unstructured to Structured data.................................................................................................................5
Data cleaning.............................................................................................................................................5
Missing value imputation..........................................................................................................................5
Data subset selection and/or subsampling.................................................................................................5
Exploratory visualization using ggplot2....................................................................................................5
Result and Discussion......................................................................................................................................6
Conclusion........................................................................................................................................................7
References.........................................................................................................................................................7
Appendix...........................................................................................................................................................8