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{"@context":"https://schema.org","@type":"DiscussionForumPosting","headline":"Objective function in SMO SVM","articleBody":"Hello jonchar,\r\n\r\nI 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 : \r\n``return np.sum(alphas) - 0.5 * np.sum(target * target * kernel(X_train, X_train) * alphas * alphas)\r\n\r\nHowever, 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. \r\n\r\nOne more time, I might be wrong, and I would really appreciate your feedback on it.\r\n\r\nBest,\r\n\r\nKilian","author":{"url":"https://github.com/kilianFatras","@type":"Person","name":"kilianFatras"},"datePublished":"2019-02-13T10:20:17.000Z","interactionStatistic":{"@type":"InteractionCounter","interactionType":"https://schema.org/CommentAction","userInteractionCount":4},"url":"https://github.com/1/ml-python/issues/1"}