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A novel estimation algorithm is introduced for logistic regression model with nonnegative coefficients constraints. The basic idea is to decompose the model parameters as a vector of convex coefficients (the multinomial manifold) and a scaling parameter, which are then optimized alternatively based on the maximum likelihood cost function. The first and second order Riemannian geometry of the multinomial...
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