Chapter 2. Clustering
This chapter explains the clustering technique in machine learning and its implementation using Apache Mahout.
The K-Means clustering algorithm is explained in detail with both Java and command-line examples (sequential and parallel executions), and other important clustering algorithms, such as Fuzzy K-Means, canopy clustering, and spectral K-Means are also explored.
In this chapter, we will cover the following topics:
- Unsupervised learning and clustering
- Applications of clustering
- Types of clustering
- K-Means clustering
- K-Means clustering with MapReduce
- Other clustering algorithms
- Text clustering
- Optimizing clustering performance
