Regression, Machine Learning, Artificial Intelligence, Linear Regression, Python.
form of a GLM can be expressed as: Y ~ f(µ) = g⁻¹(η) where Y is the response variable, f(µ) is the distribution of Y, µ is the mean of Y, g is the link function, and η is the linear predictor. In other words, GLMs assume that the response variable Y has a probability distribution that is a member