Q. Suppose you are building a SVM model on data X. The data X can be error prone which means that you should not trust any specific data point too much. Now think that you want to build a SVM model which has quadratic kernel function of polynomial degree 2 that uses Slack variable C as one of its hyper parameter.What would happen when you use very large value of C(C->infinity)? (Solved)
1. we can still classify data correctly for given setting of hyper parameter c
2. we can not classify data correctly for given setting of hyper parameter c
3. cant say
4. none of these
- a. we can still classify data correctly for given setting of hyper parameter c