For many real world problems data points to undergo unsupervised
grouping are less likely to behave crisply as their features might
overlap between different classes. Therefore fuzzy clustering
seems to be more suitable. A fuzzy clustering engine developed
through the means of evolutionary computation is proposed. The
model correctly classifies 78% of the cases.