Semi-supervised is the machine learning field. In the previous work, selection of pairwise constraints for semi-supervised clustering is resolved using active learning method in an iterative manner. Semi-supervised clustering derived from the pairwise constraints. The pairwise constraint depends on the two kinds of constraints such as must-link and cannot-link.In this system, enhanced iterative...

Clustering is an important tool for data mining, since it can identify major patterns or trends without any supervision (labeled data). Over the past five years, semi-supervised (constrained) clustering methods have become very popular. These methods began with incorporating pairwise constraints and have developed into more general methods that can learn appropriate distance metrics. However, s...

We introduce a principled method for the signed clustering problem, where goal is to partition weighted undirected graph whose edge weights take both positive and negative values, such that edges within same cluster are mostly positive, while spanning across clusters negative. Our relies on graph-based diffuse interface model formulation utilizing Ginzburg-Landau functional, based an adaptation...