APPLICATION OF SUPERVISED LEARNING
SUPPORT VECTOR MACHINE SVM
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Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
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LASSO
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Ridge
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Both
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None of these
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Detailed explanation-1: -9) Which of the following algorithms do we use for Variable Selection? In case of lasso we apply a absolute penality, after increasing the penality in lasso some of the coefficient of variables may become zero. where g(z) is the logistic function.
Detailed explanation-2: -True-False: Lasso Regularization can be used for variable selection in Linear Regression. True, In the case of lasso regression, we apply an absolute penalty which makes some of the coefficients zero.
Detailed explanation-3: -It also explains whether the covariates are collinear. Therefore, the Lasso Regularization can be used for variable selection in linear regression. Hence, the given statement is true.
Detailed explanation-4: -Lasso regression algorithm is defined as a regularization algorithm that assists in the elimination of irrelevant parameters, thus helping in the concentration of selection and regularizes the models. Lasso models can be evaluated using various metrics such as RMSE and R-Square.