Haskell Data Analysis Cookbook

Chapter 8. Clustering and Classification

This chapter demonstrates algorithms that intelligently cluster and categorize data:

• Implementing the k-means clustering algorithm
• Implementing hierarchical clustering
• Using a hierarchical clustering library
• Finding the number of clusters
• Clustering words by their lexemes
• Classifying the parts of speech of words
• Identifying key words in a corpus of text
• Training a parts-of-speech tagger
• Implementing a decision tree classifier
• Implementing a k-Nearest Neighbors classifier
• Visualizing points using Graphics.EasyPlot

Introduction

Computer algorithms are becoming better and better at analyzing large datasets. As their performance ...