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1)  werighted mean attribute significance
加权平均重要度
2)  weighted mean attribute significance
加权平均属性重要性
3)  Weight Average Methodology
权重加权平均法
4)  Weighted mean roughness
加权平均粗糙度
1.
This paper introduces the connotations of the decision tree algorithm and the method for constructing of the decision tree algorithm,improves the decision tree algorithm constructed by using the weighted mean roughness,and illustrates the advantages of the improvement algorithm with the example.
介绍了决策树算法的含义和构筑方法,对基于加权平均粗糙度构造决策树算法进行改进,通过实例说明了改进算法的优势。
2.
We presented weighted mean roughness, a new concept based on rough sets theory which is regarded as the criteria for choosing attributes.
基于粗糙集的理论提出了加权平均粗糙度的概念 ,将其作为选择分离属性的标准。
3.
In the process of constructing a decision tree, weighted mean roughness, a new concept based on rough set theory which is regarded as the criteria for choosing attributes is applied.
在构造决策树的过程中,基于粗集的理论运用了加权平均粗糙度的概念,并将其作为选择分离属性的标准。
5)  Weighted average applicability
加权平均贴近度
6)  weighted mean temperature
加权平均温度
1.
In order to eliminate the error in calculating weighted mean temperature and improve the precision of remote sensing precipitable water vapor, some different methods are introduced and compared in north China, such as in Zhangjiakou, Xingtai and Beijing.
为尽可能地减小计算加权平均温度的误差,提高地基GPS遥感大气水汽总量的精度。
补充资料:加权平均
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性质:在计算n个数x1,x2,…,xn的平均数时,如每个数在总量中所占的“重量”不同,则计算它们的平均数时就需考虑各个数的“重量”,如此得出的平均数称为加权平均。标志每个数x1在总量中所占“重量”的量称为每个数xl的权,记作p1(i=1,2,…,n)。加权平均一般指加权算术平均,设有n个数x1,x2,…,xn,各数的权分别为p1,p2,…,pn,则加权算术平均为。

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