I need to generate an equation for hyperplane, I have two independent variables and one binary dependent variable.
Regarding this following equation for svm , $f(x)=sgn( sum_i alpha_i K(sv_i,x) + b )$
I have two independent variables (say P and Q) with 130 point values for each variable. I used svm radial basis function for binary classification (0 and 1) and I calculated for radial basis kernelized case, and now I have
One column of 51 y (i) alpha (i) or (dual coefficients).
Two columns of 51 sv (support vectors)for P and Q.
- One single value for b .
I received these using scikit SVC.
So, how can I generate the equation now?
Can I multiply those 51 y (i) alpha (i) or (dual coefficients) with 51 sv (support vectors) for each variable P and Q so that I have two coefficients for P and Q so that finally my equation appears as f(x)=sgn( mP + nQ +b) where m = sum of the (product of 51 sv of P with 51 dual coefficients) and n = sum of the (product of 51 sv of Q with 51 dual coefficients)?