The invention discloses a density adaptive clustering method orienting behavior identification, and relates to the technical field of clustering analysis. The density adaptive clustering method comprises the steps that clustering analysis is performed on a given data set from the highest density threshold to the lowest density threshold according to the decreasing order. The result generated in the previous clustering process can directly act as the input of the next clustering process, and necessary correction is performed on the previous clustering result under the current density threshold so that clustering of different density data clusters can be realized. Basic clustering operators adopt the clustering method based on density, and the clustering process is the typical iterative extension process so that the disadvantages that a distance-based algorithm only can discover quasi-circular clusters can be overcome. Therefore, the method is not sensitive to noise data and can automatically eliminate influence of the noise data on the clustering process and can discover the clusters of any shapes.