Extension of the objective functions in fuzzy clustering

It is pointed out that extreme physical information provides a natural frame for the extension of the objective function based methods when applied in a non-extensive setting. This formalism provides an interpretation of parameters like for example the fuzzifier exponent m. Moreover, it is relevant to show the connection between the power and Gaussian laws and to bridge the gap between the possibilistic and probabilistic approaches in fuzzy clustering