Свободный член — параметр модели, действующий как интерсепт или сдвиг и позволяющий предсказательной функции смещаться относительно начала координат. В линейных моделях он аналогичен y-пересечению. Это техническое значение отличается от этического, социального или статистического смещения в анализе справедливости.
An intercept or offset from an origin. Bias is a parameter in machine learning models, which is symbolized by either of the following: - b - w~0~ 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. !The plot of a line with a slope of 0.5 and a bias (y-intercept) of 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.