However, support vector machine (SVM) can better solve problem of small-sample learning and provides the foundation for solving intelligent diagnosis problems.
而支持向量机能够较好地解决小样本学习问题，为解决智能诊断的这一问题提供了基础。
The main advantage of SVM is that it can serve better in the processing of small-sample learning problems by the replacement of Experiential Risk Minimization by Structural Risk Minimization.
由于使用结构风险最小化原则代替经验风险最小化原则，使它能较好地处理小样本情况下的学习问题。
Compared with statistical theory, statistical learning theory focuses on the machine learning of small sample size and can trade off between the complexity of models and generalization performance.
与传统统计学相比，统计学习理论是一种专门研究小样本情况下机器学习规律的理论。
The algorithm combines active learning, biased classification and incremental learning to model the small sample biased learning problem in relevance feedback process.
该算法将主动式学习、有偏分类和增量学习结合起来，对相关反馈过程中的小样本有偏学习问题进行建模。
As a new machine learning method, SVM can solve the small sample, nonlinear, high dimension and local minima, the actual problem.
作为一种新的机器学习方法，SV M能较好地解决小样本、非线性、高维数和局部极小点等实际问题。
SVM solves the small sample problem mainly and finds the best compromise between the complexity of the model and the learning ability in order to obtaining the best generalization ability.
SVM主要解决小样本问题，在模型的复杂度和学习能力之间寻求最佳折衷，目的在于获得最好的泛化能力。
Statistical Learning Theory is based on a solid theoretical foundation. It provides an unified framework for solving the small sample learning problem.
统计学习理论具有坚实的理论基础，为解决小样本学习问题提供了统一的框架。
Though choosing the experimental results as the learning sample, the performance predictive model of EDM micro-and-small holes is proposed, with the BP algorithm of artificial neural network.
采用人工神经网络的BP算法，以电火花微小孔加工工艺参数正交实验的结果作为神经网络的学习样本，建立电火花微小孔加工多目标工艺参数的预测模型。
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。
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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