APPLICATION OF SUPERVISED LEARNING
LINEAR REGRESSION
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Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
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What will happen when you apply very large penalty in case of Lasso?
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Some of the coefficient will become zero
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Some of the coefficient will be approaching to zero but not absolute zero
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Both A and B depending on the situation
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None of these
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Explanation:
Detailed explanation-1: -Lasso Regression (Least Absolute Shrinkage and Selection Operator) adds “absolute value of magnitude” of coefficient as penalty term to the loss function.
Detailed explanation-2: -Performs L1 regularization, i.e., adds penalty equivalent to the absolute value of the magnitude of coefficients. Minimization objective = LS Obj + * (sum of the absolute value of coefficients)
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