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
• (C) we can not classify the data at all
• (D) data can be classified correctly without any impact of c