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Regularized regression versus Ordinary Least Squares

We model life expectancy by considering how some selected variables affect life expectancy. Ordinary Least Squares regression is compared to Regularized regression to see which regression method produces the smallest mean squared error.

Lasso, Ridge and Elastic net were compared to a multiple linear regression approach. We concluded the elastic net model has the smallest mean square error.

The data was obtained from the World Health Organization.

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