1. kernel = "linear": linear SVM
   equation example : $𝑘(𝑥1,𝑥2)=𝑥𝑇1𝑥2$

2. kernel = "poly": polynomial kernel
   equation example: $𝑘(𝑥1,𝑥2)=(y(𝑥T1𝑥2)+coef0)d$

   • gamma: 𝛾
   • coef0: 𝜃
   • degree: 𝑑

3. kernel = "rbf" or kernel = None: RBF kernel. equation example: $k(𝑥1,𝑥2)=exp(−y||x1−x2||2)$

   • gamma: 𝛾

4. kernel = "sigmoid": sigmoid kernel.
   equation example:$𝑘(𝑥1,𝑥2)=tanh(y(𝑥𝑇1𝑥2)+coef0)$

   • gamma: 𝛾
   • coef0: 𝜃

(Note: In the polynomial, RBF, and sigmoid kernels, the parameter gamma specifies the level of influence that a single training example has. The larger gamma is, the more influence a single example has)