On the Stability of Shared Near Neighbor Clustering

This correspondence concentrates on the detection of stable clustering results when using the nonparmetric clustering technique of Jarvis and Patrick. This technique incorporates the concept of similarity based on sharing of near neighbors. Essentially, in this clustering scheme, two parameters are involved: neighborhood depth and similarity threshold. Combining a penalty for chaining with the detection of so-called hierarchical stable solutions in the field of all possible solutions, due to the setting of the two parameters, is experimentally shown to provide a powerful method for discriminating between reliable and unreliable results.