Machine Learning with scikit-learn Quick Start Guide

Unsupervised learning

Unsupervised learning is a form of machine learning in which the algorithm tries to detect/find patterns in data that do not have an outcome/target variable. In other words, we do not have data that comes with pre-existing labels. Thus, the algorithm will typically use a metric such as distance to group data together depending on how close they are to each other.

As discussed in the previous section, most of the data that you will encounter in the real world will not come with a set of predefined labels and, as such, will only have a set of input features without a target attribute.

In the following simple mathematical expression, U is the unsupervised learning algorithm, while X is a set of input features, such as ...