canonical base

canonical base的基本解释

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标准基, 标准基底, 典范基

与canonical base相关的网络例句 [注：此内容来源于网络，仅供参考]

The first coefficients of canonical correlation of body weight traits with body measurement traits was significant (P.01), the canonical correlation coefficient was 0.828, respectively represented 92.11% of total correlation. The first coefficients of canonical correlation of body weight traits with age-corrected and backfat thickness-corrected of weighting at 100 kg were significant (P.01), the canonical correlation coefficient 0.851, respectively represented 97.80% of total correlation. The first and second canonical correlation coefficients of body measurement traits with age-corrected and backfat thickness-corrected of weighting at 100 kg were significant (P.05), the first canonical correlation coefficient was 0.607, respectively represented 78.52% of total correlation.

体质量与体尺性状间、体质量性状与100kg体质量校正日龄和背膘厚间的第一典型相关系数均达极显著相关水平(P.01)，分别为0.828和0.85，占总相关的92.11%和97.80%；体尺性状与100kg体质量校正日龄和背膘厚间的第一、二典型相关系数达显著相关(P.05)，第一典型相关系数为0.607，占总相关的78.52%。

Abstract〕similar to regression analysis,cluster analysis,etc.,correlation analysis is also the basic work for information researches.canonical correlation analysis can be used to analyze the relationship between two groups of variables,and thus worth for using in information science.method of canonical correlation analysis was presented in present study.a java-based network algorithm of canonical correlation analysis was developed,which can be used to calculate the canonical correlation coefficients,canonical variable pairs,and statistical significance of canonical correlation coefficients.the algorithm may be run on java-compatible web browser.at the same time,paper publishing information and citation statistics in information science of china in past years were analyzed using the algorithm,and a number of conclusions were drawn.

摘 要〕与因果分析等一样，相关分析也是信息资料分析的基本工作。典范相关分析用于分析两组变量之间的关系，在情报信息的相关性分析方面有潜在的应用价值。本研究介绍了典范相关分析方法，给出了典范相关分析的java网络算法软件，可用于计算典范相关系数，典范变量对，以及典范相关系数的统计显著性。该软件可在兼容java的网络浏览器上运行。同时，用该算法对国内情报信息论文的发文和引文统计数据进行了分析，得到了一些结论。

Experimental results indicated that the first canonical correlation coefficient and the second canonical correlation coefficient was 0.8451 and 0.7843 respectively, they have constituted 91.37% of the total correlation. The first canonical variable (V1) of the response signals group had certain predicted ability on physicochemical index of milk, but the predicted ability was a little weak, response signals of ZZ sensor(X1)、CA sensor(X4) and JB sensor(X7) played a crucial role .At the same time, four canonical variable V and W have explained 42.49% and 43.25% of the total variances of the other group respectively.

试验结果表明：第一典型相关系数和第二典型相关系数分别是0.8451 和 0.7843，前两对典型变量共占总相关的91.37%；响应信号组的第一典型变量(V1)对牛奶理化指标具有一定的预测能力，但预测能力较弱，起主要作用的是ZZ传感器响应信号(X1)、CA传感器响应信号(X4)和JB传感器响应信号(X7)；与此同时，V和 W 的四个典型变量分别解释另一组变量总方差的42.49%和43.25%。

与canonical base相关的网络解释 [注：此内容来源于网络，仅供参考]

基础利率 base rate 基础利率：base rate

431 1 base price 基价 base price 基价 | 432 1 base rate 基础利率 base rate 基础利率 | 433 1 base stock 基础存量 base stock 基础存量

canonical assemblage：正则系综

canonical algebra | 典范代数 | canonical assemblage | 正则系综 | canonical bilinear form | 典范双线性型

canonical coordinates：标准坐标

canonical basis 典范基 | canonical coordinates 标准坐标 | canonical correlation coefficient 典型相关系数