Categorical Data Clustering Using Harmony Search Algorithm for Healthcare Datasets

Healthcare analytics provide many benefits in healthcare dashboard systems. datasets majorly contains categorical attributes. This paper proposed an optimized clustering for dataset named harmony search based (HSCC). The existing k-modes algorithm is one of the well-known data-clustering algorithm. Since produces local optimal clusters. Generally, researchers use genetic (GA) algorithms to converge locally solutions global solutions. GA has some deficiencies such as premature convergence with low speed. In this paper, (HS) optimization used optimize results. result shows HSCC produced solution, unbiased and matured 98% accuracy dental 71% lung cancer dataset. While GACC 95% 65%