Intro to Computational Biology
Ridge regression is a type of linear regression that includes a regularization term to prevent overfitting by penalizing large coefficients. This technique modifies the ordinary least squares method by adding a penalty equal to the square of the magnitude of the coefficients, effectively shrinking them towards zero. This approach is particularly useful when dealing with multicollinearity among predictors, as it stabilizes the estimation process and improves model performance.
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