fork download
  1. scores<-c(4,4,3,4,4,3,4,2,5,4,5,3,5,4,5,4,4,5,5,5,2,4,4,4,3,4,5)
  2. golfMatrix<-matrix(scores,nrow=9)
  3. rownames(golfMatrix)<-c("Hole 1", "Hole 2", "Hole 3", "Hole 4", "Hole 5", "Hole 6", "Hole 7", "Hole 8", "Hole 9")
  4. colnames(golfMatrix)<-c("Phil", "Tiger", "Vijay")
  5. print (golfMatrix)
  6. golfSVD<-svd(golfMatrix, nu=nrow(golfMatrix), nv=ncol(golfMatrix))
  7. golfSVD
  8. approx_Golf_1 <- golfSVD$u[,1] %*% t(golfSVD$v[,1]) * golfSVD$d[1]
  9. print (approx_Golf_1)
Success #stdin #stdout 0.46s 24680KB
stdin
Standard input is empty
stdout
       Phil Tiger Vijay
Hole 1    4     4     5
Hole 2    4     5     5
Hole 3    3     3     2
Hole 4    4     5     4
Hole 5    4     4     4
Hole 6    3     5     4
Hole 7    4     4     3
Hole 8    2     4     4
Hole 9    5     5     5
$d
[1] 21.116733  2.014004  1.423864

$u
            [,1]        [,2]        [,3]        [,4]        [,5]        [,6]
 [1,] -0.3548528  0.08912626  0.63510622  0.02415090 -0.39368790  0.23659893
 [2,] -0.3842357  0.18894413  0.10273509 -0.22710064  0.04782861 -0.57153066
 [3,] -0.2180618 -0.39604843 -0.28094945 -0.44166040 -0.14576123 -0.25498511
 [4,] -0.3567627 -0.07556623 -0.32999583  0.82355844 -0.09298384 -0.15868783
 [5,] -0.3273797 -0.17538409  0.20237530  0.01945606  0.87590065  0.12940988
 [6,] -0.3317737  0.33260802 -0.48022986 -0.22352269 -0.01309690  0.63944123
 [7,] -0.2999067 -0.43989445 -0.23035562 -0.13422444 -0.14184593  0.01083064
 [8,] -0.2774018  0.64096440 -0.09809276 -0.07470621  0.03567452 -0.27433199
 [9,] -0.4092247 -0.21923012  0.25296912  0.02432008 -0.15512419  0.16176235
             [,7]        [,8]        [,9]
 [1,] -0.08987515  0.03120815 -0.49210988
 [2,]  0.10537224 -0.64103145  0.05978576
 [3,] -0.59189539  0.22758935 -0.18220154
 [4,] -0.17094933 -0.05747638 -0.11622980
 [5,] -0.05947292  0.09580829 -0.15512419
 [6,] -0.08321240 -0.28716904 -0.01637113
 [7,]  0.75618197  0.14826422 -0.17730742
 [8,]  0.11600095  0.63642295  0.04459315
 [9,] -0.07434115  0.11976036  0.80609476

$v
           [,1]       [,2]       [,3]
[1,] -0.5276850 -0.8220644  0.2139128
[2,] -0.6204716  0.2010335 -0.7580241
[3,] -0.5801409  0.5327248  0.6161500

          [,1]     [,2]     [,3]
 [1,] 3.954119 4.649399 4.347188
 [2,] 4.281532 5.034384 4.707149
 [3,] 2.429859 2.857118 2.671405
 [4,] 3.975401 4.674423 4.370586
 [5,] 3.647987 4.289438 4.010625
 [6,] 3.696949 4.347010 4.064454
 [7,] 3.341855 3.929477 3.674061
 [8,] 3.091084 3.634611 3.398361
 [9,] 4.559984 5.361798 5.013281