Multi-Density Clustering Algorithm Based on Grid Adjacency Relation

The paper presents a multi-density clustering algorithm based on grid adjacency relation (GAMD) using data distribution characteristics within units, which is reflected by the unit density and the center of mass. In order to determine the unit boundary, the algorithm measures the similarity between units by the relative density of units and relative distance of center of mass. Goodness of fit is proposed for evaluating clustering validity. The experimental results show that the algorithm can cluster the arbitrary shape and multi-density data sets effectively. The clustering results have no relationship with data input and unit order.