OpenCV 4 with Python Blueprints - Second Edition

Briefing on supervised learning concepts

An important subfield of machine learning is supervised learning. In supervised learning, we try to learn from a set of labeled data—that is, every data sample has a desired target value or true output value. These target values could correspond to the continuous output of a function (such as y in y = sin(x)), or to more abstract and discrete categories (such as cat or dog).

A supervised learning algorithm uses the already labeled training data, analyzes it, and produces a mapping inferred function from features to a label, which can be used for mapping new examples. Ideally, the inferred algorithm will generalize well and give correct target values for new data.

We divide supervised learning tasks ...