From 4a36feb8c0ac922cb58ab9eebe028a62536522b7 Mon Sep 17 00:00:00 2001 From: Morten Hjorth-Jensen Date: Mon, 17 Jul 2023 22:56:19 +0200 Subject: [PATCH] Create notes.txt --- doc/src/Bayesian/notes.txt | 15 +++++++++++++++ 1 file changed, 15 insertions(+) create mode 100644 doc/src/Bayesian/notes.txt diff --git a/doc/src/Bayesian/notes.txt b/doc/src/Bayesian/notes.txt new file mode 100644 index 000000000..4e45d6031 --- /dev/null +++ b/doc/src/Bayesian/notes.txt @@ -0,0 +1,15 @@ +A group of machine learning algorithms where the fits and optimizations are based on Bayesian statistics (Bayes’ Theorem) instead of traditional statistics and optimizations +Assume outputs can be described as distributions instead of as linear and nonlinear combinations of inputs and hyperparameters are fit using priors instead of being set by user +Benefits: No hyperparameter tuning, no validation data set, produced uncertainties on predictions + + +Bayesian Ridge Regression +Bayesian version of ridge regression (regularized linear regression) +Finds parameters and hyperparameters using Gaussian distributions +Different results than ridge regression but does not depend on user-ser hyperparameter + + +Gaussian Processes +Bayesian version of kernel ridge regression or support vector machines +Similar to Bayesian ridge regression but uses the kernel trick to modify the inputs +Kernel: Modified Rational Quadratic Kernel