Background: A common clustering method in the analysis of gene expression data has been hierarchical clustering. Usually the analysis involves selection of clusters by cutting the...
Clustering, in data mining, is useful to discover distribution patterns in the underlying data. Clustering algorithms usually employ a distance metric based (e.g., euclidean) simi...
Clustering belongs to the set of mathematical problems which aim at classification of data or objects into related sets or classes. Many different pattern clustering approaches bas...
Faezeh Ensan, Mohammad Hossien Yaghmaee, Ebrahim B...
Document clustering has been used for better document retrieval, document browsing, and text mining in digital library. In this paper, we perform a comprehensive comparison study ...
The diameter k-clustering problem is the problem of partitioning a finite subset of Rd into k subsets called clusters such that the maximum diameter of the clusters is minimized. ...