Logistic regression is a probabilistic, linear classifier. It is parametrized by a weight matrix W and a bias
vector b. Classification is done by projecting an input vector onto a set of hyperplanes, each of which
corresponds to a class. The distance from the input to a hyperplane reflects the probability that the input is
a member of the corresponding class.