Table of contents : Title Page Table of Contents Part I - Introduction Chapter 1 - Introduction to R Chapter 2 - Introduction to Machine Learning Part II - Classification Chapter 3 - Classification with Decision trees Chapter 4 - Classification with Naive Bayes Chapter 5 - Classification with k-Nearest Neighbors Chapter 6 - Classification with Support Vector Machines Part III - Data Processing Chapter 7 - Feature Selection Chapter 8 - Dimensionality Reduction Part III - Clustering Chapter 9 - Centroid-based Clustering and Evaluation Chapter 10 - Connectivity-based Clustering Chapter 11 Density-based Clustering Chapter 12 - Distribution-based Clustering Part V - Extended Topics Chapter 13 - Association Rules