...份分析之方法，做为股票技术指标的筛选并利用支援向量回归(Support Vector Regression)及支援向量分类(Support Vector Classify)之方法运用于台湾股票市场股价波动之预测，其实验结果皆达六成以上，甚至有些股票公司之预测正确更是高达七成，显示SVMs方法运用...
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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。
The way of fault Diagnoses based on Support Vector Machine has a simple model compared with the traditional method. It also has great ability to classify, and the best generalization.
与传统的故障诊断方法相比，基于支持向量机的故障诊断方法具有模型简单、分类能力强、推广能力好等特点。
Then, support vector machine is selected to classify aiming at clinical ECG data. Finally, classifications combination approach is analyzed.
随后针对实际的临床十二导联心电图数据，实验了两种支持向量机的分类方法。
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