Efficient Analysis of Pharmaceutical Compound Structure Based on Enhanced K-Means Clustering Algorithm
In this paper to focuses on discovery of functional group of the connectivity atom for drug effects of chemical compound structured data with position of each atom. A simple Kmeans algorithm, select an initial centroid distance randomly for analysing the data. In the proposed method an Enhanced K means algorithm, forms a functional group of inter connected atoms based on calculate initial centroid distance instead of random selected. The pharmaceutical compounds specifically represented as atom number, atom name like carbon, hydrogen, nitrogen, oxygen with connected atoms. Here it can be experimented the number of iterations are reduced and performance of time accuracy can improve when compare with chameleon and Birch algorithm.