For example using one attribute: during learning phase, we assigned each example point to the appropriate
cluster. Each cluster represents one distribution. After finishing the training phase, if we are given a point, the
algorithm can assign this point to one of the existing distribution. If we use infinite training, then any point
given by user is also classified to the appropriate distribution and it is also considered as a new training point.