1) sum square error
误差平方和法
3) square sum of studying error
学习误差平方和
1.
In this paper, relevant parameters influencing sample training precision are explored when the mixtures of experts networks is applied to boiler fault diagnosis,and the relationahip between the square sum of studying error and some parameters,such as rule numbers、studying rate、cycle numbers、weighted exponent,are presented.
探讨了将混合专家网络应用于锅炉故障诊断时,影响样本训练精度的有关参数,得出了规则数、学习率、循环次数、加权指数等参数与样本训练学习误差平方和之间的关
4) sum-of-squared-error criterion
误差平方和准则
1.
In this paper,we propose an unsuperviset strategy(UKNNC)for the KNN Classifier,which adopts sum-of-squared-error criterion to adaptively select the contributing part from these neighbors and classifies the input document in term of the disturbance degree which it brings to the kernel den.
该方法先采用误差平方和准则自适应地从k个最近邻居所包含的各类别中挑选与输入文档于同一簇的部分邻居作为参照,然后根据输入文档对各类参照邻居核密度的扰动程度进行分类。
5) forecasting error square sum
预测误差平方和
1.
The purpose of this paper is to compare the upper limits of forecasting error square sum in equal weight forecasting and weighted equal weight forecasting by mathematical induction, and analyze the effectiveness of equal weight forecasting.
用数学归纳法对简单平均法与简单加权平均法的预测误差平方和的上界进行了比较,对简单平均法的有效性进行了分析。
6) sum of square of error QE
误差平方和QE
1.
repeatedly measure m times for each point,to constitute new number pairs(xi,■),to build improved a linear regression modely=β0+β1xi+■■~N(0,σ2/m),to decompose the sum of square of residuals Qε into sum of square of error QE and sum of square of variation of repeat observation QL.
采用重复观测的方法,即对每个测量点重复m次的方法,组建新的数对(xi,■),建立改进的一元线性回归模型y=β0+β1xi+■■~N(0,σ2/m),对残差平方和Qε进行分解为误差平方和QE和重复观测变异平方和QL。
补充资料：误差平方和
分子式：
CAS号：
性质：表示实验误差大小的偏差平方和。在相同的条件下各次测定值xi对测定平均值x的偏差平方后再加和∑(xi-x)2。
CAS号：
性质：表示实验误差大小的偏差平方和。在相同的条件下各次测定值xi对测定平均值x的偏差平方后再加和∑(xi-x)2。
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