Research of Grid-Similarity-Based Clustering Algorithm

Aim at the limitations of traditional measurement method on similitude between objects, we put forward grid-similarity-based clustering algorithm (GSCA), it brings in a new criterion to measure the similitude between objects. It applies on the grid clustering and disposes the density threshold of grid by the method of density threshold that improves the precision of clustering. Besides, the GSCA algorithm disposes the very high dimension datasets by the technique of entropy. The algorithm appears its advantages in the comparative experiments with some traditional clustering algorithm.