Active Learning of Pair-wise Constraints in Semi-supervised Clustering
Lihong Wang · Journal of Guangxi Normal University · 2011
An active learning method of pair-wise constraints based on error correction is proposed in this paper,and stopping criterion is also presented in order to get better clustering result with less pair-wise constraints.Experiments on the UCI benchmark datasets and artificial datasets show that the performance of semi-supervised clustering algorithm with the proposed strategy is better than that of compared strategies.In addition,the clustering result of each tested dataset is acceptable under the stopping criterion.