Lecture

Ridge Regression: Penalised Least Squares

In course

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Description

This lecture covers Ridge Regression, a method to handle multicollinearity in linear models by adding a 'ridge' to the design matrix. It standardizes the design matrix and replaces ZT Z by ZTZ+AI to stabilize inversion. The lecture also discusses the shrinkage viewpoint of Ridge Regression, the bias and variance tradeoff, and the LASSO method as a relaxation of best subsets selection.

Instructors (2)

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Official source

https://mediaspace.epfl.ch/media/0_fuy1p7d3

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Ontological neighbourhood

Statistics

Data analysis: Regression analysis, Cross-validation

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