Ridge Regression with cross-validation in Python

A Ridge Regression demo for optimization and hyper-parameter tuning for regression models in R


Ridge Regression Ridge Regression is a hyper-parameter tuning technique that helps us deal with multi-collinearity and variance in regression models. Here, we use cross-validation to provide a robust OLS estimation with variance taken into account. This allows us to have the benefits of polynomial regression (low bias), while penalizing high-variance to find a balanced model that has a good fit, but generalizes well to new data.

Further Reading: A great article on Ridge Regression Fundamentals

Jupyter Notebook via Gist

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