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Regularization

 Regularization

Regularization is a technique helps to reduce overfitting.In this technique our bias increase little bit but variance improve so much.

Working 

You know y=mx+b is line where m defines slope but in terms of machine learning it defines say/weightage of x in model.

If m is very high it is overfitting or m is very low then model is underfitted . In summary we want to set correct value of m.In regularization we just decrease m.

To do it add term called "regularization term"  in our loss function

There are 3 types of regularization

  1. Ridge Regression(L2)
  2. Lasso Regression(L1)
  3. ElasticNet Regression

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