基于统计学理论研究了经验风险最小化原则学习过程的一致性问题。
We describe the consistency of erm learning process instatistical learning theory .
由于采用了结构风险最小化原则替代经验风险最小化原则，使它能较好地解决小样本学习问题。
It can solve small samples learning problems better by using structural risk minimization in place of experiential 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。
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.
针对基于经验风险最小化原则的传统学习方法的不足，提出了一种基于支持向量机的油气管道安全识别方法。
An SVM-based recognition method for the safety of oil and gas pipeline was proposed due to limitation of the traditional learning methods based on empirical risk minimization.
支持向量机是以统计学习理论为基础的，采用结构风险最小化原则代替传统经验风险最小化原则的新型统计学习方法。
It is a new statistical study method in which the traditional empirical risk minimization principle is replaced by structural risk minimization principle.
结构风险最小化归纳原则通过控制经验风险和置信范围来控制实际风险的界。
Structural risk minimization induce principle is used to control the bound on the value of achieved risk by controlling experiential risk and belief bound at the same time.
结构风险最小化归纳原则通过控制经验风险和置信范围来控制实际风险的界。
Structural risk minimization induce principle is used to control the bound on the value of achieved risk by controlling experiential risk and belief bound at the same time.
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