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