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1·The method of constructing the lower confidence limit is based on sample space ordering.

利用样本空间排序法给出了参数优良的置信下限与计算置信下限的递推公式。

2·Then it builds a model by partial least squares regression on the obtained sample space.

在相对合理的样本空间中采用偏最小二乘回归建立模型。

3·Since we know one of the children is a girl, we will drop the Boy-Boy possibility from the sample space.

因为我们已经知道其中有一个女孩，我们就可以去掉男孩-男孩的可能性。

4·As for the undivided linear sample space, the kernel function is needed to map onto another high dimension linear space.

对于线性不可分的样本空间，需要寻找核函数，将线性不可分的样本集映射到另一个高维线性空间。

5·Sample space order method is used to give the lower confident limits of mean life under unequal time truncations for exponent distribution.

使用样本空间排序法给出了指数分布情形下不相同定时截尾试验平均寿命置信下限的估计方法。

6·Basic idea is to adoption of non-linear transform, so that after changing the characteristics of the sample space become linearly separable.

基本思想是通过非线性变换，使样本变换之后的特征空间中变得线性可分。

7·Both algorithms take advantage of the communication relationship with the neighbor node, build the sample space, to improve the positioning accuracy.

这两种算法均利用邻居节点间的通讯约束关系构建样本空间，从而提高算法的定位精度。

8·A new adaptive variable neural network is developed according to the inner product feature of sample space. This method does not need to iterate learning.

根据样本空间的内积特性，提出一种无需迭代学习的自适应变结构神经网络。

9·In the case of K type interval censored data, the lower confidence limit of parameter is studied based on the order relation established in the sample space.

基于K型区间删失数据，利用样本空间排序法给出参数优良的置信下限和计算置信下限的递推公式。

10·During the statistical process of density, the probability density distribution of the rock mass structural plane in sample space is assumed as normal distribution.

在密度统计过程中，把岩体结构面样本在空间上的概率密度分布假设成正态分布。