How can Ridge Regression be used to mitigate multicollinearity in Multiple Linear Regression?
- By adding a penalty term to the coefficients
- By increasing model complexity
- By reducing the number of samples
- By removing correlated variables
Ridge Regression adds a penalty term to the coefficients, shrinking them and mitigating the impact of multicollinearity. This regularization technique helps stabilize the estimates.
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