Clustering Techniques

So far, we've been performing supervised learning. There have been labels we wished to predict correctly, and values we wished to approximate closely with a function, and were unable to. Now, we'll look at an entirely different topic, which will be the focus of both this chapter and the next: unsupervised learning, starting with clustering. This chapter starts with a brief discussion on the difference between supervised and unsupervised learning, and specifically, what clustering is. After that, we'll look at our first clustering algorithm: the k-means algorithm, a popular and simple algorithm. Before exploring some other algorithms, we'll discuss approaches to evaluating a clustering scheme. Then, we'll move on to the next two approaches for clustering; the first being hierarchical clustering. The final clustering approach we&apos...