Nvidia Interview Question | Ridge Regression
Question
When might you want to use ridge regression instead of traditional linear regression? State some situations.
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Answer ( 1 )
Ridge regression allow us to regularize coefficients. This means that the estimated coefficients are pushed towards 0, to make them work better on new data-sets
Ridge regression is often used when the independent variables are colinear. One issue with colinearity is that the variance of the parameter estimate is huge. Ridge regression reduces this variance at the price of introducing bias to the estimates
Ridge Regression, avoids over fitting by adding a penalty to models that have too large coefficients.