title: why is SVM a "black box" learning algorithm?
body: <p>I'm going through Andrew Ng's Machine Learning course on Coursera, and in the intro to his section on SVM's he says: "SVMs are considered by many to be the most powerful 'black box' learning algorithm"</p>
  
  <p>He doesn't elaborate on that. Why would SVM's be considered a black box? Is it because their behavior is less straightforward than that of, say, logistic regression?</p>