Hello jonchar,

I was reading your notebook on solving SVM with SMO algorithm. Unfortunately there is a part that I might misunderstand and looks as an error to me. When you define your objective function, you return :
``return np.sum(alphas) - 0.5 * np.sum(target * target * kernel(X_train, X_train) * alphas * alphas)

However, I think the term (target * target) is target^2 (element wise multiplication) instead of a matrix composed of target_i * target_j. To agree with the theory, I would have coded target[:,None] * target[None,:] to get such matrix.

One more time, I might be wrong, and I would really appreciate your feedback on it.

Best,

Kilian