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Vladimir N.Vapnik等提出的统计学习理论(statistical learning theory,简称SLT)和支持向量机(support vector machine,简称SVM)算法已取得令人鼓舞的研究成果。本文旨在对这一新理论和新算法的原理作一介绍,并展望这一计算机学界的新成果在化学化工领域的应用前景。“ChemSVM”软件提供了通用的支持向量机算法,并将其与数据库、知识库、原子参数及其他数据挖掘方法有机地集成起来。
The statistical learning theory (SLT) and support vector machine (SVM) algorithms proposed by Vladimir N.Vapnik et al. Have achieved encouraging research results. The purpose of this paper is to introduce the principles of this new theory and new algorithm and to look forward to the application prospects of this new achievement of computer science in the field of chemical chemistry. The “ChemSVM” software provides a common SVM algorithm and integrates it with databases, repositories, atomic parameters, and other data mining methods.