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Python Data Science Essentials - Second Edition by Luca Massaron, Alberto Boschetti

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An overview of unsupervised learning

In all the methods we've seen so far, every sample or observation has its own target label or value. In some other cases, the dataset is unlabeled and, in order to extract the structure of the data, you need an unsupervised approach. In this section, we're going to introduce two methods to perform clustering, as they are among the most used methods for unsupervised learning.

Note

It is useful to keep in mind that often the terms "clustering" and "unsupervised learning" are considered synonymous, though actually unsupervised learning has a larger meaning.

The first method that we'll introduce, named K-means, is the most commonly used clustering algorithm despite its inevitable shortcomings. In signal processing, ...

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