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Data Science Using Python and R
book

Data Science Using Python and R

by Chantal D. Larose, Daniel T. Larose
April 2019
Beginner to intermediate content levelBeginner to intermediate
240 pages
6h 47m
English
Wiley
Content preview from Data Science Using Python and R

Chapter 3DATA PREPARATION

3.1 THE BANK MARKETING DATA SET

We will illustrate how to perform the first two phases of the Data Science Methodology using the bank_marketing_training and bank_marketing_test data sets. Readers may download these data sets from the book series web site: www.dataminingconsultant.com. These data sets are adapted from the bank‐additional‐full.txt data set1 from the UCI Machine Learning Repository.2 We use only four predictors (age, educations, previous_outcome, and days_since_previous), plus the target, response. The data relate to a phone‐based direct marketing campaign conducted by a bank in Portugal. The bank was interested in whether or not the contacts would subscribe to a term deposit account with the bank. The bank_marketing_training data set contains 26,874 records, while bank_marketing_test contains 10,255 records.

3.2 THE PROBLEM UNDERSTANDING PHASE

We begin with the Problem Understanding Phase, in order to make sure that the ladder we are working so hard to climb is not leaning against the wrong wall.

3.2.1 Clearly Enunciate the Project Objectives

The objectives of this analysis are as follows:

  1. Learn about our potential customers. That is, learn the characteristics of those who choose to bank with us, as well as those who do not.
  2. Develop a profitable method of identifying likely positive responders, so that we may save time and money. That is, develop a model or models that will identify likely positive responders. Quantify the expected ...
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Publisher Resources

ISBN: 9781119526810Purchase book