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Table 5. Reproducibility Using PCA: Ratio of Between-Run and Within-Run residualsa

in Output
by Systematische Sichtweise, Verschiedene Strategien, Inputs Säulenmaterial

TABLE 6 PRINCIPAL COMPONENTS

in Do Crosscutting Concerns Cause Defects? Marc Eaddy, Student Member, IEEE, Thomas Zimmermann, Student Member, IEEE,
by Kaitlin D. Sherwood, Vibhav Garg, Gail C. Murphy, Ieee Computer Society, Alfred V. Aho

Table 1. Principal component analysis

in
by Alireza Panahi, Qiuming Cheng, Graeme F. Bonham-carter
"... In PAGE 9: ... 60% of the total variability of the data (Fig. 6, Table1 ). The first principal component accounts for c.... ..."

Table 2: First principal components

in Visualizing Stylistic Variation
by Jussi Karlgren, Troy Straszheim 1997
Cited by 15

Table 3: Principal Component Matrix

in Early Estimation of Software Quality Using InProcess Testing Metrics
by Laurie Williams, Mladen Vouk, Jason Osborne 2005
Cited by 3

TABLE IX PRINCIPAL COMPONENT SCORES.

in Quantitative Assessment of User-Level QoS and its Mapping
by Yoshihiro Ito, Shuji Tasaka

Table 5 Principal component loadings

in Abstract Multivariate statistical evaluation of trace elements in groundwater in a coastal area in Shenzhen, China
by Kouping Chen A, Jiu J. Jiao A, Jianmin Huang B, Runqiu Huang B 2006
"... In PAGE 7: ... The PCA was carried out by diagonalization of the correlation matrix, so the prob- lem of different numerical ranges of the original variables was avoided, since all variables were scaled to variance unit and contributed equally. Table5 summarized the PCA results including the loadings and the eigenvalues of each PC. There were several criteria to identify the number of PCs to be re- tained in order to understand the underlying data structure (Jackson, 1991).... ..."

Table 9: Principal components for component C

in Using Historical In-Process and Product Metrics for Early Estimation of Software Failures
by Thomas Ball, Brendan Murphy
"... In PAGE 8: ... The extracted code base for Component C for Windows XP-SP1 was 1820 KLOC (consisting of 3265 files). Based on PCA three principal components out of the six generated that account for greater than 95% of the variance as shown in Table9 are used for building the statistical multiple and logistic regression models. Table 9: Principal components for component C ... ..."
Cited by 1

Table 1: Results of principal component analysis applied to the correlation matrix of the vegetation-soil characteristics in the study area. For abbreviations and units, see Appendix Axis Eigenvalue % of Variance Cum. % of Var. Broken-stick Eigenvalue

in Soil-Vegetation Relationships in Hoz-e-Soltan Region of Qom Province, Iran
by M. Jafari, M. A. Zare Chahouki, A. Tavili, H. Azarniv
"... In PAGE 2: ... Results PCA: In order to find the most effective factors on the separation of vegetation types, PCA was used. As it is shown in Table1 , PC1 and PC2 are accounted for 70.95% of vegetation variations that is caused by soil characteristics.... ..."

Table 7: Principal components for component A

in Using Historical In-Process and Product Metrics for Early Estimation of Software Failures
by Thomas Ball, Brendan Murphy
Cited by 1
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