A Novel Grid-Based Clustering Algorithm

Abstract Data clustering is an important method used to discover naturally occurring structures in datasets. One of the most popular approaches grid-based concept algorithms. This kind characterized by a fast processing time and it can also clusters arbitrary shapes These properties allow these methods be many different applications. Researchers have created versions using approach. However, key issue right choice number grid cells. paper proposes novel algorithm which uses for automatic determining based on k dist function computes distance between each element dataset its th nearest neighbor. Experimental results been obtained several datasets they confirm very good performance newly proposed method.