Using the same data, build a Support vector Machine Linear Classifier,

a$)$ show your code and parameters selection, $(10$pts$)$

b$)$ find the Support Vectors defining the separation hyperplane, $(10$pts$)$

c$)$ Beta $($weights$)$ and bias$($intercept$)$ values defining SVM classifier $(10$pts$)$

$($Just for home work purposes, you can assume this is the training data, you

have another set of data for testing $)$