虚拟样本生成技术研究

虚拟样本生成技术主要研究如何利用待研究领域的先验知识并结合已有的训练样本构造辅助样本，扩充训练样本集，提高学习器的泛化能力。作为一种在机器学习中引入先验知识的方法，虚拟样本生成技术已经成为提高小样本学习问题泛化能力的主要手段之一，受到了国内外学者广泛研究。首先介绍了虚拟样本的概念，给出了衡量虚拟样本生成技术性能的两个指标，讨论了虚拟样本生成技术对学习器泛化能力的影响。然后根据虚拟样本生成技术的本质将其划分为3类，并针对每一类讨论了几种典型的虚拟样本生成技术，进而指出了现有虚拟样本生成技术存在的一些不足。最后进行总结并对虚拟样本生成技术的进一步发展提出了自己的看法。

Research on Virtual Sample Generation Technology

Virtual sample generation technology mainly makes research on how to combine the priori knowledge of a domain with the existing training samples to create additional training samples, enlarging the training dataset, and improving the generalization ability of learning machine. As a method of bringing priori knowledge to machine learning, virtual sample generation technology has become a primary means to improve the generalization ability on small sample learning problem, and has been studied widely by scholars home and abroad. In this paper, firstly the concept of virtual sample was introduced, two indexes of evaluating the capability of virtual sample generation technology were given, and the influence of virtual sample generation technology on the generalization ability of learning machine was discussed.Then the current virtual sample generation technologies were divided into 3 classes by their essence, and for each class several typical virtual sample generation technologies were discussed. Moreover the deficiencies of the current virtual sample generation technology were pointed out Finally, made a summary and proposed our own viewpoint on the further development of virtual sample generation technology.