Enhancing data analysis through k-means with foggy centroid selection

Clustering algorithms have emerged as indispensable tools across diverse sectors such as engineering, ecommerce, and healthcare in the contemporary era. Among the prominently utilized methods, k-means, fuzzy c-means, and hierarchical clustering have garnered substantial attention The effectiveness of these algorithms hinges on their ability to discern data clusters through inter-centroid calculations can leverage the extraction of high utility itemsets from databases that prioritize value-oriented information. These applications encompass a wide