On Linear Clustering with Constraints on Cluster Size

Clustering is unsupervised classification method in the field of machine learning. c-varieties (CV) and c-regression (CR) are linear clustering that can find linear structures of a dataset. CV and CR are clustering algorithms that perform principal component analysis and regression analysis at the same time, respectively. By the way, when clustering is used in the actual society, there are situations where the number of objects in each cluster is restricted. In this paper, we propose new linear clustering algorithms with constraints on cluster size.