Hands-On Machine Learning for Algorithmic Trading

Supervised learning

Supervised learning is the most commonly used type of ML. We will dedicate most of the chapters in this book to learning about the various applications of models in this category. The term supervised implies the presence of an outcome variable that guides the learning process—that is, it teaches the algorithm the correct solution to the task that is being learned. Supervised learning aims at generalizing a functional relationship between input and output data that is learned from individual samples and applying it to new data.

The output variable is also, depending on the field, interchangeably called the label, target, outcome, endogenous, or left-hand-side variable. We will use y_i for observations i = 1, ..., N, or ...