Nonsmooth DC programming approach to clusterwise linear regression: optimality conditions and algorithms. (2nd January 2018) - Bagirov, A.M.; Ugon, J.
Abstract : The clusterwise linear regression problem is formulated as a nonsmooth nonconvex optimization problem using the squared regression error function. The objective function in this problem is represented as a difference of convex functions. Optimality conditions are derived, and an algorithm is designed based on such a representation. An incremental approach is proposed to generate starting solutions. The algorithm is tested on small to large data sets.