R for Data Science Cookbook

Chapter 12. Unsupervised Machine Learning

This chapter covers the following topics:

• Clustering data with hierarchical clustering
• Cutting trees into clusters
• Clustering data with the k-means method
• Clustering data with the density-based method
• Extracting silhouette information from clustering
• Comparing clustering methods
• Recognizing digits using density-based clustering methods
• Grouping similar text documents with k-means clustering methods
• Performing dimension reduction with Principal Component Analysis (PCA)
• Determining the number of principal components using a scree plot
• Determining the number of principal components using the Kaiser method
• Visualizing multivariate data using a biplot

Introduction

The unsupervised machine learning method focuses on revealing ...