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Created by dmitriybugaichenko on 24.03.16.
Implementation for multi-class logistic regression training. In contrast to traditional notion of multi-class logistic regression this trainer produces one regression per each class. Internally treats all classes simultaneously using matrix-matrix multplication. Allows for L1-regularization (switches LBFGS to OWL-QN for that). Regularization strength is defined in terms of fraction of maximal feasible regularization (deduced using http://jmlr.org/papers/volume8/koh07a/koh07a.pdf).