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Are Perceptrons like linear support vector machines, but just without the constraint that the hyperplane has to lie at the maximum margin distance from the poin
by gcr 15y ago
Are Perceptrons like linear support vector machines, but just without the constraint that the hyperplane has to lie at the maximum margin distance from the points?
- mebassett 15y agoI don't think I yet know enough about SVMs to answer your question, but the two are quite similar. Both perceptrons and SVMs classify data by separating it with a hyperplane. I think the difference is in the learning algorithm used: perceptrons' learning method just keeps moving the plane until the good/bad points are on the right side. SVMs learning method does try to ensure that the hyperplane lies at the max margin distance from classified points. I think. :)