Bayesian Linear Regression

A linear regression approach that treats model parameters as probability distributions rather than fixed values.

Bayesian Linear Regression places uncertainty at the center of the model. While classical linear regression estimates coefficients as single values, the Bayesian version estimates distributions over them. This enables richer interpretation through uncertainty quantification, interval estimation, and risk analysis, especially in small-data settings. It provides a strong advantage in domains where decision quality depends on explicitly modeling uncertainty.