bias (math) or bias term

An intercept or offset from an origin. Bias is a parameter in machine learning models, which is symbolized by either of the following: - b - w0 For example, bias is the b in the following formula:

In a simple two-dimensional line, bias just means "y-intercept." For example, the bias of the line in the following illustration is 2. Bias exists because not all models start from the origin (0,0). For example, suppose an amusement park costs 2 Euros to enter and an additional 0.5 Euro for every hour a customer stays. Therefore, a model mapping the total cost has a bias of 2 because the lowest cost is 2 Euros. Bias is not to be confused with bias in ethics and fairness or prediction bias. See Linear Regression in Machine Learning Crash Course for more information.

Practitioners refer to bias (math) or bias term when building, training, or evaluating machine learning systems. It appears in research papers, product documentation, and technical discussions about AI capabilities and limitations.