During the training, these nodes are adjusted to represent the distribution of the classes in the
feature space. After the training, the nodes are labeled. During the classification, classes of the input
vectors are determined according to the one-nearest neighbor rule, i.e., the class of the input vector
is assigned as the class of the nearest vector to the input vector.