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1)  rank score
秩打分
1.
To screen for molecular signatures that are commonly dysregulated in subtypes of a certain cancer,a novel meta-analysis is designed to perform rank score (RS) on lists of genes that are derived from different studies.
针对筛选特定癌症亚型的特异表达基因,提出了一种新颖的癌症基因芯片的后综分析方法——运用并改进秩打分算法(RS),对有序基因列表的统计均值取秩并打分。
2)  Rank analysis
秩分析
1.
In this article,we propose the method of rank analysis to evaluate the differences between categories of the ordinal data in data mining,and then apply the cluster analysis to the quantification of the ordinal data.
本文针对数据挖掘中的多分类有序资料,提出了用秩分析的方法对其间距差异作出界定。
3)  Rank [英][ræŋk]  [美][ræŋk]
分位秩
1.
The Estimation of the Ranks Based on Monte-Cario Simulation and it's Performation with Computer;
Monte-Carlo模拟估计分位秩的方法在计算机上的实现
4)  full rank decomposition
满秩分解
1.
Based on the two simple alternative practical methods of the full rank decomposition and Gaussian elimintion,this paper was primarily concerning with the algorithms for some generalized invers
在两种可供选择的满秩分解方法和Gauss消元法的基础上,主要研究了某些广义逆的计算。
2.
And all of these approaches are derived from the full rank decomposition technique for the incidence matrix.
这些方法都是基于网关联矩阵的满秩分解。
3.
Based on matrix s elementary row operation remaining its column vector s linear relationship and Hermite standard form of matrix,the paper gives a simple method for solving full rank decomposition of matrix only through elementary row operation.
利用矩阵初等行变换不改变矩阵列向量组线性关系的性质,以及矩阵的Hermite标准形,给出了一种只通过初等行变换可求得矩阵满秩分解的简单方法。
5)  low-rank decomposition
低秩分解
1.
A low-rank decomposition technique is adopted to transform the standard semidefinite programming into an equivalent nonlinear programming problem.
首先采用低秩分解技术将一般的半定规划问题转化为与其等价的非线性规划问题;然后利用多目标优化中的占优概念,来建立一个有效的筛子,使目标函数和不可行性达到最优,建立了半定规划的筛选法;最后给出了算法的收敛性分析。
2.
Methods A low-rank decomposition technique is adopted to transform the general semidefinite programming into an equivalent nonlinear programming problem.
方法采用低秩分解技术将一般的半定规划问题转化为与其等价的非线性规划问题,利用基于方向分解的筛选算法,通过对搜索方向进行切线步和垂直步的分解来分别寻求最优解方向和不可行性改善的方向,构造了半定规划问题的筛选算法。
6)  full rank factorization
满秩分解
1.
The full rank factorization and Moore-Penrose inverse for generalized row(column) unitary symmetric matrix
广义行(列)酉对称矩阵的满秩分解及其Moore-Penrose逆
2.
The concept of row (column) transposed matrix and row (column) symmetric matrix is given,their basic property is studied,and the formula for full rank factorization and orthogonal diagonal factorization of row (column) symmetric matrix are presented,which can reduce dramatically the amount of calculation and save the CPU time and memory without loss of any numerical precision.
提出了行(列)转置矩阵与行(列)对称矩阵的概念,研究了其性质,给出了行(列)对称矩阵的满秩分解和正交对角分解公式,极大地减少了行(列)对称矩阵的满秩分解和正交对角分解的计算量与存储量,且没有降低数值精度。
3.
In addition,the formulas of the full rank factorization,rank factorization and generalized inverse of row (column) antisymmetric matrix are given,which make calculation easier and accurate.
利用分块矩阵理论获得了许多新的结果,给出了行(列)反对称矩阵的满秩分解、秩分解和广义逆的公式及快速算法。
补充资料:秩分
1.官位名分。
说明:补充资料仅用于学习参考,请勿用于其它任何用途。
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