风险最小化原则 meaning in Chinese
principle of minimization risk
principleofminimizationrisk
Examples
- It can solve small - sample learning problems better by using experiential risk minimization in place of structural risk minimization
由于采用了使用结构风险最小化原则替代经验风险最小化原则，使它较好的解决了小样本学习的问题。 - Because of the lack of training samples , traditional methods based on experiential risk minimization can not play well in recognizing the characters
由于训练样本不足,决定了采用传统的基于经验风险最小化原则的识别方法难以取得较好的识别效果。 - This method can be used to small scale recognition , like artificial neural networks , but it has stronger generalization ability because the support vector machine theory is based on the minimization principle to structure risk
该方法与人工神经网络一样适用予小规模分类，但由于支持向量机依据结构风险最小化原则，因此泛化能力更强。 - An novel support vector regression ( svr ) algorithm based on structural risk minimization inductive principle instead of empirical risk minimization principle was firstly introduced in well logs intelligent analysis
摘要基于核学习的支持向量机，是一种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，具有完备的理论基础。 - Especially , the support vector machine ( svm ) text classification algorithm is discussed . we introduce the linear svm and the nonlinear svm and analyze the reason that svm is superior to other methods in theoretical
分类算法是文本分类的关键，介绍了线性支持向量机和非线性支持向量机，从结构风险最小化原则得到了支持向量机优于其它方法的结论。