试验结果表明该方法是有效、可行的，且在小样本情况下比BP神经网络具有更高的诊断精度。
The test shows that this method is effective and feasible, and has higher diagnosis precision than BP neural network in cases of fewer samples.
支持向量机方法能够解决小样本情况下非线性函数拟合的通用性和推广性的问题，是求复杂的非线性拟合函数的一种非常有效的技术。
The problems of universality and extensibility in nonlinear function approximation using small samples can be solved by the method, it a very efficient technique for nonlinear function approximation.
提出一种在小样本的情况下，基于多层贝叶斯网络的医学图像语义建模方法。
A semantic modeling approach for medical image semantic retrieval based on hierarchical Bayesian networks was proposed, in a small set of samples.
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