Fuzzy clustering algorithms like the popular fuzzy c-means algorithm (FCM) are
frequently used to automatically divide up the data space into fuzzy granules. When the fuzzy clusters are used to derive membership functions for a fuzzy rule-based system,then the corresponding fuzzy sets should fulfill some requirements like boundedness of support or unimodality.(Problems may also arise in the case, when the fuzzy partition
induced by the clusters is intended as a basis for local function approximation. In this
case, a local model (function) is assigned to each cluster. Taking the fuzziness of the
partition into account, continuous transitions between the single local models can be
obtained easily.)