We extend the VC theory of statistical learning to data dependent spaces of classifiers. This theory can be viewed as a decomposition of classifier design into two components; the...
Adam Cannon, J. Mark Ettinger, Don R. Hush, Clint ...
In this paper, we introduce a novel objective function for the hierarchical clustering of data from distance matrices, a very relevant task in Bioinformatics. To test the robustnes...
Pritha Mahata, Wagner Costa, Carlos Cotta, Pablo M...
The application of document clustering to information retrieval has been motivated by the potential effectiveness gains postulated by the Cluster Hypothesis. The hypothesis states ...
— Social network analysis has been used for quite some time to analyze and understand the behavior of nodes in the network. Theses nodes could be individuals or group of persons,...
Despite of the large number of algorithms developed for clustering, the study on comparing clustering results is limited. In this paper, we propose a measure for comparing cluster...