An incremental clustering algorithm based on grid

The existing clustering algorithms based on grid are analyzed, and the clustering algorithms based on grid have the advantages of dealing with high dimensional data and high efficiency. However, traditional algorithms based on grid are influenced greatly by the granularity of grid partition. An incremental clustering algorithm based on grid, which is called IGrid, is proposed. IGrid has the advantage of high efficiency of traditional clustering algorithms based on grid, and it also partition the grid space by dimensional radius in a dynamic and incremental manner to improve the quality of clustering. The experiments on real datasets and synthetic datasets show that IGrid has better performance than traditional clustering algorithms based on grid in both speed and accuracy.