Chapters
1: Introduction
2: Recommendation systems
3: Item-based filtering
4: Classification
5: More on classification
6: Naïve Bayes
7: Unstructured text
8: Clustering

Clustering

This chapter looks at two different methods of clustering: hierarchical clustering and kmeans clustering.

Contents

• what is clustering
• hierarchical clustering
• single-linkage, complete-linkage, average-linkage
• clustering dog breeds
• clustering breakfast cereals
• kmeans clustering
• kmeans++
• Clustering Enron Email

The PDF of the Chapter

Python code

• hierarchicalClustererTemplate.py (p 20)
• hierarchicalClusterer.py (p 21)
• kmeans.py (p 40)
• kmeansPlusPlus.py (p 54)

Data

• dog.csv (dog breed example)
• dogDistanceSorted.txt
• cereal.csv (breakfast cereals)
• mpg.txt (car mpg data)
• enrondata.txt (Enron from-to counts data)
• mongodb dump of entire Enron data (> 300mb)