Unsupervised learning is a type of machine learning that looks for previously undetected patterns in a data set with no pre-existing labels and with a minimum of human supervision.
In contrast to supervised learning that usually makes use of human-labeled data, unsupervised learning, also known as self-organization allows for modeling of probability densities over inputs.
It forms one of the three main categories of machine learning, along with supervisedand reinforcement learning.
Semi-supervised learning, a related variant, makes use of supervised and unsupervised techniques.
