In SVM which has quadratic kernel function of polynomial degree 2 that has slack variable C as one hyper paramenter. What would happen if we use very large value for C

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Q. In SVM which has quadratic kernel function of polynomial degree 2 that has slack variable C as one hyper paramenter. What would happen if we use very large value for C

(A) we can still classify the data correctly for given setting of hyper parameter c

(B) we can not classify the data correctly for given setting of hyper parameter c

(D) data can be classified correctly without any impact of c

Correct : Option (A)

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Q. In SVM which has quadratic kernel function of polynomial degree 2 that has slack variable C as one hyper paramenter. What would happen if we use very large value for C

Discusssion

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