Why do we use Ridge regression instead of Least squares in Multicollinearity?
Which one is correct:
a. lower bias and higher variance
b. lower bias with the same variance
c. higher bias with a lower variance
d. the same bias with lower variance
Solved – Why we use Ridge regression instead of Least squares in Multicollinearity
biasleast squaresmulticollinearityridge regressionself-study
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Best Answer
Why would we use ridge regression? It's useful because it prevents overfit to your training data. Now, ask yourself how does preventing overfit influence bias and variance.
I have a useful link for you: When to use regularization methods for regression?