Linear Models

The linear_models module includes:

1. OLS linear regression with maximum likelihood parameter estimates via the normal equation.
   • Includes optional weight arguments for weighted least squares
   • Supports batch and online coefficient updates.
2. Ridge regression / Tikhonov regularization with maximum likelihood parameter estimates via the normal equation.
3. Logistic regression with maximum likelihood parameter estimates via gradient descent.
4. Bayesian linear regression with maximum a posteriori parameter estimates via conjugacy
   • Known coefficient prior mean and known error variance
   • Known coefficient prior mean and unknown error variance
5. Naive Bayes classifier with Gaussian feature likelihoods.
6. Generalized linear model with identity, log, and logit link functions.

Plots

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