...rly separable case )、线性支持向量机(linear support vector machine)及非线性支持向量机(non-linear support vector machine)。 学习方法包括： 硬间隔最大化(hud margin maximization)、软间隔最大化(soft margin maximization)、核技巧(kernel trick)。
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Support vector machine is a kind of machine study algorithm based on statistic theory, it has special advantage in solving small sample, non-linear and high dimension mode recognition.
支持向量机是一种基于统计理论的机器学习算法，在解决小样本、非线性及高维模式识别中有独特的优势。
Chaos and support vector machine theory has opened up a new route to study complicated and changeable non-linear hydrology time series.
混沌和支持向量机理论为研究复杂多变的非线性水文时间序列开辟了新的途径。
Experimental results indicate that the support vector machine performs a number of unique advantages in solving the small sample size, non-linear problems.
经过实验证明支持向量机在解决小样本、非线性问题中表现出很好的优势。
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