weidiaoyu的博客

机器学习，模式识别领域的资料，主要是概率推理。

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.

介绍了多目标优化问题，使用进化算法求解是较好方式。