An improved initialisation method for K-means algorithm optimised by Tissue-like P system

摘要

The K-means algorithm gets widely used due to its simplicity and effectiveness. But it is sensitive to the selection of initial cluster centres. In this paper, we proposed an initialisation method to select initial clustering centres for K-means algorithm. Furthermore, because of the boundedness of the initialisation method, we modified it and designed a Tissue-like P system to realise the new method. The experiments are operated on five UCI datasets and the results proved that the new initialisation method based on the designed Tissue-like P system is effective.