Practical Data Analysis Cookbook

Chapter 3. Classification Techniques

In this chapter, we will cover various techniques that will allow you to classify the outbound call data of a bank. You will learn the following recipes:

• Testing and comparing the models
• Classifying with Naïve Bayes
• Using logistic regression as a universal classifier
• Utilizing Support Vector Machines as a classification engine
• Classifying calls with decision trees
• Predicting subscribers with random tree forests
• Employing neural networks to classify calls

Introduction

In this chapter, we will be classifying the outbound calls of a bank to see if such a call will result in a credit application. We will use the dataset described in A Data-Driven Approach to Predict the Success of Bank Telemarketing. Decision Support Systems ...