OLA interview Question | Regularization
Question
Explain what regularization is and why it is useful?
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Machine Learning
4 years
1 Answer
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Answer ( 1 )
In simple terms, regularization is about introducing a little bias in your model,
so that it generalizes well over the test data. In Linear Regression, regularization
tries to shrink the coefficients towards zero. It discourages learning a more complex
model to avoid over-fitting.