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Log(loss) is convex, which means that we can use gradient descent to find weights that result in a global minimum. 0 / 1 loss is not convex due to its abrupt decision boundary at z = 0, so it is difficult to optimize.

data_mining/convex.txt · Last modified: 2015/07/13 21:49 by gerardnico