Intermediate · Data
Generalized linear model
Visual diagram · (in preparation) · Math · (in preparation) · Worked example · 3 difficulty levels.
TL;DR. A flexible regression model that generalizes standard linear regression to accommodate different error distributions and link functions, allowing it to model a wider range of data types.
Technical Definition
A flexible regression model that generalizes standard linear regression to accommodate different error distributions and link functions, allowing it to model a wider range of data types.
How it works
Generalized Linear Models (GLMs) extend the basic linear regression framework, which assumes normally distributed errors. GLMs allow for response variables that have error distribution models other than a normal distribution, such as Poisson or binomial distributions. They use a 'link function' to connect the linear predictor to the mean of the response variable, making them suitable for categorical or count data.
Related Concepts
- Regression — A supervised learning task that predicts a continuous numeric value.
- Optimization — The mathematical process of finding parameter values that minimize a loss function.