Knowledge based (re-)clustering
Matthew C. Clark, Lawrence Hall, Chunlin Li, Dmitry B. Goldgof · 2002
This paper presents a novel multiparadigm segmentation method based upon knowledge based clustering with reclustering. The techniques described enhance unsupervised classification and achieve pattern labeling. First domain knowledge is utilized to decide where and how a clustering algorithm is applied, then clustering is iteratively applied to focus-of-attention patterns with the knowledge of how many expected classes there are in those patterns and the prototypical patterns of a class. Examples showing clustering improvements are given from brain MRI's and satellite images.