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

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

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we can not classify the data at all

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data can be classified correctly without any impact of c

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

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