Similarity learning is a supervised learning area focused on learning how alike or related two objects are. It supports tasks such as ranking, recommendation, face verification, speaker verification, identity matching, and retrieval.
An area of supervised learning closely related to classification and regression, but the goal is to learn from a similarity function that measures how similar or related two objects are. It has applications in ranking, in recommendation systems, visual identity tracking, face verification, and speaker verification.