文件名称：Multiobjective Supervised Learning
文件大小：1.23MB
文件格式：PDF
更新时间：2013-10-22 16:00:50
多目标优化 进化算法 多目标学习
This chapter sets out a number of the popular areas in multiobjective supervised learning. It gives empirical examples of model complexity optimization and competing error terms, and presents the recent advances in multi-class receiver operating characteristic analysis enabled by multiobjective optimization. It concludes by highlighting some specific areas of interest/concern when dealing with multiobjective supervised learning problems, and sets out future areas of potential research.