>> - a class for regression and one for classification >> - MSE and cross entropy (for classification only) loss functions > We need several loss functions and there gradient in cython (we cannot > reuse the loss function from the SGD module of since the output of a > MLP can be a multi-variate). For classification we will need hnigeloss > and squared hingeloss (and hubert for regression). See the source of > libsgd for a list of useful loss function. > > Can you explain how hinge-loss works for multiple classes? Or would you train a separate mlp for each class?
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