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Soft margin is not as good as hard margin

This note is a link to an excerpt from my upcoming monster support vector machine article (where I work through a number of sections of [Vapnik, 1998] Vapnik, V. N. (1998), Statistical Learning Theory, Wiley). I try to run down how the original theoretical support vector machine claims are precisely […]

The Geometry of Classifiers

As John mentioned in his last post, we have been quite interested in the recent study by Fernandez-Delgado, et.al., “Do we Need Hundreds of Classifiers to Solve Real World Classification Problems?” (the “DWN study” for short), which evaluated 179 popular implementations of common classification algorithms over 120 or so data […]