5. Performing Your First Cluster Analysis
Overview
By the end of this chapter, you will be able to load and visualize data and clusters with scatter plots; prepare data for cluster analysis; perform centroid clustering with k-means; interpret clustering results and determine the optimal number of clusters for a given dataset.
This chapter will introduce you to unsupervised learning tasks, where algorithms have to automatically learn patterns from data by themselves as no target variables are defined beforehand.
Introduction
The previous chapters introduced you to very popular and extremely powerful machine learning algorithms. They all have one thing in common, which is that they belong to the same category of algorithms: supervised learning. ...
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