Python Machine Learning Cookbook

Chapter 2. Constructing a Classifier

In this chapter, we will cover the following recipes:

• Building a simple classifier
• Building a logistic regression classifier
• Building a Naïve Bayes classifier
• Splitting the dataset for training and testing
• Evaluating the accuracy using cross-validation
• Visualizing the confusion matrix
• Extracting the performance report
• Evaluating cars based on their characteristics
• Extracting validation curves
• Extracting learning curves
• Estimating the income bracket

Introduction

In the field of machine learning, classification refers to the process of using the characteristics of data to separate it into a certain number of classes. This is different from regression that we discussed in the previous chapter where the output is a real number. ...