Method for determining optimal number of clusters in K-means clustering algorithm

K-means clustering algorithm clusters datasets according to the certain clustering number k.However k cannot be confirmed beforehand.A new clustering validity index was designed from the standpoint of sample geometry.Based on the index a new method for determining the optimal clustering number in K-means clustering algorithm was proposed.Theoretical research and experimental results demonstrate the validity and good performance of the above-mentioned algorithm.