Nightly kernel regression testing.
持续多日的内核回归测试。
The kernel regression method now is the most popular non-parametric estimation method.
核回归方法是比较常用的一种非参数估计方法。
Applying the method of kernel regression, this paper puts forward a type of nonlinear model of stock volumes with prices.
利用核回归方法，建立股票成交量与价格的非线性分析模型。作为模型的应用，提出强弱弹性指数概念。
According to the chaotic characteristic of power load, fuzzy support vector based kernel regression method is proposed for load forecasting.
根据电网负荷混沌性的特点，提出一种基于模糊支持向量的核回归方法进行电力系统的负荷预测。
Perhaps there should be a corollary to Linus' Law stating that some bugs are shallower than others, because those are exactly the ones that nightly kernel regression testing weeds out.
或许Linus法则应该有这样一个结论，有一些缺陷比其他缺陷更容易被发现，因为那些正是持续多日的内核回归测试所发现并处理的那些。
This paper introduced the selection principle and method about a reasonable kernel function and bandwidth based on the nonparametric kernel density estimation and kernel regression estimation.
本文基于非参数核密度估计与核回归估计的基础上，介绍了合理选取核函数及窗宽的原则和方法。
The basic imaging model is discussed, and a novel algorithm based on steering kernel regression method as a regularization term for super resolution reconstruction of sequence image is proposed.
讨论了图像成像的基本模型，并提出了一种基于调整核回归函数作为正则项的序列图像重建算法。
During the 2.5 development cycle, another project undertaken by the Linux test project involved using the LTP test suite to perform nightly regression testing of the Linux kernel.
在2.5的开发周期中，Linux测试项目所采用的另一个项目是，用LTP测试套件对Linux内核执行持续多日的回归测试。
SVM can deal with nonlinear problems in classification and Regression easily by using kernel functions.
通过引入核函数，支持向量机可以很容易地实现非线性算法。
The kernel estimate of nonparametric regression function has been researched recently.
非参数回归函数的核估计近年来已有了一些研究。
Based on the locally kernel weighted least squares fit of the nonparametric regression models, this paper presents the nonparametric testing method for nonlinear cointegration.
本文基于非参数回归模型的局部核权最小二乘法提出变量间非线性协整的一种非参数检验方法。
Using linear programming technique and scaling kernel function, the support vector regression model was obtained.
通过线性规划技术和采用尺度函数作为核函数来实现支持向量回归模型。
Kernel Methods are concerned with mapping input data into a higher dimensional vector space where some classification or regression problems are easier to model.
核函数方法关心的是怎样把输入数据映射到一个高维度的矢量空间，在这个空间中，某些分类或者回归问题可以较容易地解决。
Kernel Methods are concerned with mapping input data into a higher dimensional vector space where some classification or regression problems are easier to model.
核函数方法关心的是如何把输入数据映射到一个高维度的矢量空间，在这个空间中，某些分类或者回归问题可以较容易地解决。
To further improve the calibration precision of the previous regression algorithms, an iterative local algorithm of color calibration based on kernel partial least squares regression is proposed.
为进一步提高回归算法的色彩校正精度，提出一个基于核偏最小二乘回归的局部迭代算法。
A new scaling kernel support vector regression was proposed for nonlinear system identification problem.
提出一种新的尺度核支持向量回归方法，并应用于非线性系统辨识问题。
This paper gives a new kernel estimate, bandwidth parameter and the bias-corrected confidence belt for nonparametric regression curve.
对非参数回归曲线提出了一种新的核估计量和窗宽选择方法及修正偏倚置信带。
In addition, an adaptive kernel relevance vector machine based on PSO is presented to deal with the problem that the regression performance of classical RVM is often influenced by kernel parameters.
此外，针对相关向量机回归计算结果受核参数影响较大的问题，本文还提出一种基于微粒群算法的相关向量机核参数自适应优化方法。
The result of multiple regression showed that ear diameter, ear rows, 1000 kernel weight and plant height with grain yield were significant.
逐步回归表明：穗粗、穗行数、千粒重、株高对产量的影响达到显著水平。
The result of multiple regression showed that ear diameter, ear rows, 1000 kernel weight and plant height with grain yield were significant.
逐步回归表明：穗粗、穗行数、千粒重、株高对产量的影响达到显著水平。
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