A c-fuzzy means algorithm for prototype induction
J.F. Baldwin, Jonathan Lawry · 2002
A c-fuzzy means algorithm is described. The algorithm learns fuzzy prototypes to represent data sets and is based on ideas taken from mass assignment theory. The potential of this approach for both unsupervised and supervised learning is illustrated by its application to a number of benchmark and model problems.