Python: End-to-end Data Analysis

Chapter 5. Clustering

With data comprising of several separated distributions, how do we find and characterize them? In this chapter, we will look at some ways to identify clusters in data. Groups of points with similar characteristics form clusters. There are many different algorithms and methods to achieve this with good and bad points. We want to detect multiple separate distributions in the data and determine the degree of association (or similarity) with another point or cluster for each point. The degree of association needs to be high if they belong in a cluster together or low if they do not. This can of course, just as previously, be a one-dimensional problem or multi-dimensional problem. One of the inherent difficulties of cluster finding ...