You are dealing with a dataset having many irrelevant features. How would you apply Lasso regression to deal with this scenario?
- By increasing the degree of the polynomial
- By using L1 regularization
- By using L2 regularization
- By using both L1 and L2 regularization
Lasso regression applies L1 regularization, which can shrink the coefficients of irrelevant features to exactly zero. This effectively performs feature selection, removing the irrelevant features from the model and simplifying it.
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