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About Lecture Notes On Ridge Regression
This document provides lecture notes on ridge regression for high-dimensional linear regression problems where the number of variables (p) exceeds the number of samples (n). It introduces standard linear regression and discusses how ridge regression modifies the model to accommodate high-dimensional data by imposing a penalty on the size of the regression coefficients. The notes cover ridge regression estimation and properties, relationships to Bayesian regression, extensions like generalized ridge regression, and comparisons to other regularization methods like the lasso.
Detailed Information
| Author: | ['Marc Romaní'] |
|---|---|
| Publication Year: | 2021 |
| Pages: | 113 |
| Language: | English |
| Format: | |
| Price: | FREE |
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