The aim of this paper is to develop an algorithm for solving the clusterwise linear least absolute deviations regression problem.This problem is formulated as a nonsmooth nonconvex optimization problem,and the objecti...The aim of this paper is to develop an algorithm for solving the clusterwise linear least absolute deviations regression problem.This problem is formulated as a nonsmooth nonconvex optimization problem,and the objective function is represented as a difference of convex functions.Optimality conditions are derived by using this representation.An algorithm is designed based on the difference of convex representation and an incremental approach.The proposed algorithm is tested using small to large artificial and real-world data sets.展开更多
基金the Australian Research Council under Discovery Projects(No.DP140103213).
文摘The aim of this paper is to develop an algorithm for solving the clusterwise linear least absolute deviations regression problem.This problem is formulated as a nonsmooth nonconvex optimization problem,and the objective function is represented as a difference of convex functions.Optimality conditions are derived by using this representation.An algorithm is designed based on the difference of convex representation and an incremental approach.The proposed algorithm is tested using small to large artificial and real-world data sets.
