1) minimizing the average risk
平均风险最小化
2) risk minimization
风险最小化
1.
According to the security investment theory of Markowitz,this paper presents aCaculation method of portfolio investment under the risk minimization,and some mathematic expres-sions of the efficient frontier for portfolio investment are conducted.
根据马科维兹的证券投资理论，提出了风险最小化下证券组合投资的计算方法，给出了证券组合有效边界的数学表示，并证明了此有效边界是平面上的一条抛物线。
2.
We discuss the problem of portfolio investment with risk minimization subject to nonnegative investment proportional coefficient.
研究非负投资比例系数约束条件下,实现风险最小化的组合证券投资问题。
3) structural risk minimization
结构风险最小化
1.
Study on noise reduction in singular value decomposition based on structural risk minimization;
基于结构风险最小化原则的奇异值分解降噪研究
2.
SVM(Support Vector Machine) is a structural risk minimization principle based on classification algorithm,and it has achieved higher generalization performance with small number of samples than other classification algorithms due to its perfect theoretical properties.
SVM(SupportVectorM ach ine)是一种基于结构风险最小化原则的分类算法,由于其完善的理论基础使其在小样本模式识别中表现出比其他算法更好的泛化能力。
4) structure risk minimization
结构风险最小化
1.
In the model,instead of traditional ERM the principle of structure risk minimization(SRM) is used to fully mine the information of original data.
本文提出一种基于最小二乘支持向量机的中长期负荷组合预测模型,该模型利用结构风险最小化原则代替传统的经验风险最小化,充分挖掘原始数据和单一预测模型的信息,以单一模型的预测数据作为组合预测样本,选择多项式核函数的最小二乘支持向量机进行组合预测。
2.
Support Vector Machine is a learning technology based on structure risk minimization and a predictive tool with better generalization ability,and it effectively solute the fewer samples,nonlinear,high dimension and local minima.
支持向量机是基于结构风险最小化原理的一种学习技术,是一种具有很好泛化能力的预测工具,它有效地解决小样本、非线性、高维数、局部极小等问题。
3.
based on structure risk minimization rule, has attracted widely attention in the area of machine learning.
近年来，基于统计学习理论，兼顾模型的经验风险和置信范围的基于结构风险最小化原则已成为机器学习研究热点之一。
6) empirical risk minimization
经验风险最小化
1.
The empirical risk minimization and the structural risk minimization in machine learning are analyzed.
介绍机器学习的表示方式,分析和比较机器学习中经验风险最小化原则和结构风险最小化原则,引出用于回归估计的支持向量机,并用数学方式阐述其基本思想,讨论支持向量机技术发展中存在的主要问题。
补充资料：最小辐亮度与最小辐照度(见核爆炸火球)
最小辐亮度与最小辐照度(见核爆炸火球)
minimum-brightness and minimum-irradiance
zuixiao fuliangdu yu zuixiaofu乙haodu最小辐亮度与最小辐照度(minimum-brightness and而nimum一irradianee)见核爆炸火球。
说明：补充资料仅用于学习参考，请勿用于其它任何用途。
参考词条