Machine Learning with Swift

Unsupervised learning

In unsupervised learning, you don't have the labels for the cases in your dataset. Types of tasks to solve with unsupervised learning are: clustering, anomaly detection, dimensionality reduction, and association rule learning.

Sometimes you don't have the labels for your data points but you still want to group them in some meaningful way. You may or may not know the exact number of groups. This is the setting where clustering algorithms are used. The most obvious example is clustering users into some groups, like students, parents, gamers, and so on. The important detail here is that a group's meaning is not predefined from the very beginning; you name it only after you've finished grouping your samples. Clustering also ...