The constrained clustering algorithms developed so far mainly use these constraints in two ways (Davidson and Basu, 2006). One way is to use them as background knowledge during data partitioning and ...

In the pattern recognition subspace method, the researcher has paid more attention to extract feature subspace, then expressed individual prototype with the training sample mean. Because the number of ...

Active Constraint Learning (ACL) is continuously gaining popularity in the area of constrained clustering due to its ability to achieve performance gains via incorporating minimal feedback from a ...

The team proposed a constrained Clustering with Weak Label Prior (CWLP) to consider compound weak label prior in an integrated framework.

In this study, we propose a mining cut clustering model based on Mixed Integer Linear Programming (MILP). Then we solve it by an exact approach and by Constraint Programming (CP), analyzing the ...