Abstract
We begin by showing that the modified partition coefficient (MPC) is an average Euclidean distance between membership degrees and the centre of the fuzzy c-partition. Subsequently, we construct alternative MPCs using several other measures of dissimilarity and examine how differently they perform when compared with the original proposal. Empirical evidence shows that the MPC based on a Chernoff’s measure of divergence is more robust to the initial conditions of the fuzzy c-means algorithm.
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