Generalized Linear Models: A Framework For Flexible Machine Learning Prediction 1

Generalized Linear Models (GLMs) are a powerful and flexible framework for machine learning prediction. They are a type of regression model that can be used to predict a wide range of outcomes, from binary outcomes to continuous outcomes. GLMs are particularly useful when the data is non-linear or when the relationship between the predictor variables and the outcome is not well understood. GLMs can also be used to model complex relationships between predictor variables and the outcome, allowing for more accurate predictions. GLMs are widely used in many areas, including finance, marketing, and healthcare.