pub type MultiLogisticRegression<F> = LogisticRegressionParams<F, Ix2>;
Expand description

A multinomial class logistic regression model.

The output labels can map to any discrete feature space, since the algorithm calculates the likelihood of a feature vector corresponding to any given outcome using the softmax function softmax(x) = exp(x) / sum(exp(xi))

l2 regularization is used by this algorithm and is weighted by parameter alpha. Setting alpha close to zero removes regularization and the problem solved minimizes only the empirical risk. On the other hand, setting alpha to a high value increases the weight of the l2 norm of the linear model coefficients in the cost function.