Glossary term
Glossary term
Safety and Alignment
A generalization of least squares regression models, which are based on Gaussian noise, to other types of models based on other types of noise, such as Poisson noise or categorical noise. Examples of generalized linear models include:
multi-class regression
least squares regression
The parameters of a generalized linear model can be found through convex optimization.
Generalized linear models exhibit the following properties:
The average prediction of the optimal least squares regression model is equal to the average label on the training data.
The average probability predicted by the optimal logistic regression model is equal to the average label on the training data.
The power of a generalized linear model is limited by its features. Unlike a deep model, a generalized linear model cannot "learn new features."
Created for this library
An insurance team uses a generalized linear model with a Poisson link to estimate claim frequency per policyholder.
A risk team uses a generalized linear model with a logit link as the production credit scorecard because regulators are familiar with the form.
A healthcare analytics team uses a generalized linear model with a gamma link for length-of-stay forecasting with heavy-tailed targets.
Definition source: Google for Developers Machine Learning Glossary | Creative Commons Attribution 4.0 License