y = w^t*x + b
label, parameter of the plane
w^t*x + b = 1
w^t*x + b = 0
w^t*x + b = -1
y = {-1, +1}
w^t*x1 + b = 1
w^t*x2 + b = -1
w^t(x1-x2)/||w|| = 2/||w|| margin
max 2/||w|| while classifying everything correctly
yi(w^t*x + b) >= 1
min 1/2 ||w||^2 quadratic programming
w(α) = Σi αi – 1/2 Σio αi*αu*yi*yu*xi^t*xu
s.t. αi>=Θ, Σi αi*yi = Θ
SVMs: Linearly Married
– margins : generalization overfitting
– big is better
– optimization problem for finding max margins: QPs
– support vectors
