Robust regression techniques are recommended instead of ordinary least square regression.
推荐的稳健回归技术,而不是普通最小二乘回归。
The robust regression analysis (RRA) is such one kind quite commonly used and the effective data actuation method.
稳健回归分析(RRA),就是这样一种相当常用与有效的数据驱动方法。
Robust regression analysis and minimax residual error analysis are two aspects in data processing of dynamic measurement.
在动态测试数据处理中,常常要进行稳健回归分析和最小最大值回归分析。
You can carry out different types of robust regression analysis when your data are not suitable for conventional multiple regression analysis.
在定量的构效关系研究中,多重回归分析选人的参数,多是用穷举所有方程实现的。
A motion based segmentation scheme for image motion estimation is proposed using variable order parameterized models of image motion and robust regression.
借助于图像运动的变阶参数模型和鲁棒回归分析,提出一种基于运动分割的图像运动估计方法。
Methods We introduce a robust principal component regression based on MVT and LMS to detect outliers, and compare methods using a practical example.
方法采用基于MVT和LMS方法的一种稳健主成分回归方法来诊断异常点,并结合实例进行方法的对比。
A robust parameters estimation algorithm is proposed in this paper, which is based on uniform design for a linear regression model in the case of its coefficient matrix with random disturbance.
针对一个线性回归模型的系统矩阵存在的随机扰动情况,提出一种基于均匀设计的稳健参数估计算法。
Consequently, the learning mechanism of the proposed approach is much easier than the robust support vector regression networks (RSVRNs) approach and the weighted LS-SVMR approach.
我们所提出的方法在整个学习架构上要比强健式支援向量机网路与权重式最小平方支援向量机回归法更简易。
Based on robust statistics, robust approaches are represented for these fuzzy regression models, and are illustrated with several examples in order to show the robustness of the suggested approaches.
就这两类回归模型,从稳健统计的角度提出相应的稳健方法,并通过例子与现有的方法进行比较,说明所提方法的稳健性。
So we introduced and used quantile regression method, which was robust in this situation.
本文将使用相对于最小二乘法更具有稳健性的分位点回归估计法。
Presents a robust estimate for the linear regression of sensor output characteristic based on the robustness of least absolute deviation estimate.
利用最小一乘估计的稳健性,给出了传感器输出特征线性化的特征直线的稳健估计。
Second the properties which a cost function should have in order to construct a robust support vector regression are discussed. Then a family of cost functions is introduced.
然后讨论了构建稳健支撑向量机的代价函数所需的性质,并在此基础上,引入了损失代价函数族;
Second the properties which a cost function should have in order to construct a robust support vector regression are discussed. Then a family of cost functions is introduced.
然后讨论了构建稳健支撑向量机的代价函数所需的性质,并在此基础上,引入了损失代价函数族;
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