While running SVC(), how we can hyper tune C vs gamma combination?
I could see changes in C and gamma are impacting the accuracy differently. Also what i understand about C and gamma are :
1) C is the cost of mis-classification means large C gives you low bias and high variance. Low bias because you penalize the cost of mis-classification a lot.A small C gives you higher bias and lower variance.
2) Gamma controls the shape of the "peaks" where you raise the points. A small gamma gives you a pointed bump in the higher dimensions, a large gamma gives you a softer, broader bump.So a small gamma will give you low bias and high variance while a large gamma will give you higher bias and low variance.