An Efficient Incremental Algorithm for Clustering Based on Density
Li Fang · Jisuanji gongcheng · 2006
An incremental algorithm of high efficiency for clustering based on density is presented.The main idea consists of following:(1) Sample data by using partition and sampling technology.(2) Clustering data based on density and grid.(3) In the case for threshold adjusting,it proposes an incremental algorithm to recalculate data affected only.(4) After data insertion or deletion in dynamic environment,making use of incremental algorithm to re-cluster data.The experiments show that the new algorithm can efficiently process high dimensional data with noise and speed up mining greatly.