R: Recipes for Analysis, Visualization and Machine Learning

Chapter 4. Classification (I) – Tree, Lazy, and Probabilistic

In this chapter, we will cover the following recipes:

• Preparing the training and testing datasets
• Building a classification model with recursive partitioning trees
• Visualizing a recursive partitioning tree
• Measuring the prediction performance of a recursive partitioning tree
• Pruning a recursive partitioning tree
• Building a classification model with a conditional inference tree
• Visualizing a conditional inference tree
• Measuring the prediction performance of a conditional inference tree
• Classifying data with a k-nearest neighbor classifier
• Classifying data with logistic regression
• Classifying data with the Naïve Bayes classifier

Introduction

Classification is used to identify a category of new observations ...