.. index:: single: bayesian_ridge_regression
.. _bayesian_ridge_regression/0:

.. rst-class:: right

**object**

``bayesian_ridge_regression``
=============================

Bayesian ridge regression regressor supporting continuous and mixed-feature datasets using evidence maximization and posterior uncertainty over coefficients. Learns from a dataset object implementing the ``regression_dataset_protocol`` protocol and returns a regressor term that can be used for prediction, predictive-distribution queries, and export as predicate clauses.

| **Availability:** 
|    ``logtalk_load(bayesian_ridge_regression(loader))``

| **Author:** Paulo Moura
| **Version:** 1:0:0
| **Date:** 2026-05-07

| **Compilation flags:**
|    ``static, context_switching_calls``


| **Imports:**
|    ``public`` :ref:`regressor_common <regressor_common/0>`
| **Uses:**
|    :ref:`format <format/0>`
|    :ref:`linear_algebra <linear_algebra/0>`
|    :ref:`list <list/0>`
|    :ref:`numberlist <numberlist/0>`
|    :ref:`population <population/0>`
|    :ref:`type <type/0>`

| **Remarks:**
|    (none)

| **Inherited public predicates:**
|     :ref:`options_protocol/0::check_option/1`  :ref:`options_protocol/0::check_options/1`  :ref:`regressor_protocol/0::check_regressor/1`  :ref:`options_protocol/0::default_option/1`  :ref:`options_protocol/0::default_options/1`  :ref:`regressor_protocol/0::diagnostic/2`  :ref:`regressor_protocol/0::diagnostics/2`  :ref:`regressor_protocol/0::export_to_clauses/4`  :ref:`regressor_protocol/0::export_to_file/4`  :ref:`regressor_protocol/0::learn/2`  :ref:`regressor_protocol/0::learn/3`  :ref:`options_protocol/0::option/2`  :ref:`options_protocol/0::option/3`  :ref:`regressor_protocol/0::predict/3`  :ref:`regressor_protocol/0::print_regressor/1`  :ref:`regressor_protocol/0::regressor_options/2`  :ref:`options_protocol/0::valid_option/1`  :ref:`options_protocol/0::valid_options/1`  :ref:`regressor_protocol/0::valid_regressor/1`  

.. contents::
   :local:
   :backlinks: top

Public predicates
-----------------

.. index:: predict_distribution/3
.. _bayesian_ridge_regression/0::predict_distribution/3:

``predict_distribution/3``
^^^^^^^^^^^^^^^^^^^^^^^^^^

Predicts the posterior predictive Gaussian distribution for a new instance using the learned regressor. The returned term has the shape ``gaussian(Mean, Variance)`` where ``Variance`` includes the learned observation noise variance and coefficient posterior uncertainty only; the intercept is not treated as a probabilistic parameter.

| **Compilation flags:**
|    ``static``

| **Template:**
|    ``predict_distribution(Regressor,Instance,Distribution)``
| **Mode and number of proofs:**
|    ``predict_distribution(+compound,+list,-compound)`` - ``one``


------------

.. index:: weight_variances/2
.. _bayesian_ridge_regression/0::weight_variances/2:

``weight_variances/2``
^^^^^^^^^^^^^^^^^^^^^^

Returns the posterior marginal variances of the encoded feature coefficients in encoder order. Encoded features dropped from fitting because they had zero variance are reported with posterior variance zero.

| **Compilation flags:**
|    ``static``

| **Template:**
|    ``weight_variances(Regressor,Variances)``
| **Mode and number of proofs:**
|    ``weight_variances(+compound,-list(float))`` - ``one``


------------

Protected predicates
--------------------

(no local declarations; see entity ancestors if any)

Private predicates
------------------

(no local declarations; see entity ancestors if any)

Operators
---------

(none)

.. seealso::

   :ref:`linear_regression <linear_regression/0>`, :ref:`ridge_regression <ridge_regression/0>`, :ref:`lasso_regression <lasso_regression/0>`, :ref:`elastic_net_regression <elastic_net_regression/0>`, :ref:`gaussian_process_regression <gaussian_process_regression/0>`, :ref:`knn_regression <knn_regression/0>`, :ref:`regression_tree <regression_tree/0>`, :ref:`random_forest_regression <random_forest_regression/0>`, :ref:`gradient_boosting_regression <gradient_boosting_regression/0>`