To solve the problem that support vector machine(SVM) can only classify the small samples set, a new algorithm which applied SVM to density clustering is proposed.
为了解决支持向量机的分类仅应用于较小样本集的问题，提出了一种密度聚类与支持向量机相结合的分类算法。
A machine which can fertilize, cover soil and sow in turf was designed by theoretical analysis and test study. The machine can form a complete set with a small tractor.
通过理论分析和试验研究，设计了一种集施肥、覆土、播种于一体的草坪建植机械，该机与小型拖拉机相配套。
Support vector machine (SVM) based on the structural risk minimization of statistical learning theory is a method of machine learning for small sample set.
基于统计学习理论中结构风险最小化原则的支持向量机是易于小样本的机器学习方法。
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