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Data X:
0.771 493.000 58.972 54.281 0.751 481.000 59.249 63.654 0.766 462.000 63.955 68.918 0.754 457.000 53.785 58.686 0.773 442.000 52.760 67.074 0.781 439.000 44.795 60.183 0.793 488.000 37.348 54.326 0.791 521.000 32.370 54.085 0.878 501.000 32.717 53.564 0.873 485.000 40.974 60.873 0.897 464.000 33.591 53.398 0.885 460.000 21.124 45.164 0.796 467.000 58.608 59.672 0.776 460.000 46.865 56.298 0.788 448.000 51.378 62.361 0.786 443.000 46.235 56.930 0.801 436.000 47.206 62.954 0.811 431.000 45.382 62.431 0.801 484.000 41.227 52.528 0.781 510.000 33.795 54.060 0.778 513.000 31.295 53.093 0.759 503.000 42.625 52.695 0.764 471.000 33.625 52.333 0.754 471.000 21.538 41.747 0.749 476.000 56.421 58.576 0.729 475.000 53.152 57.851 0.740 470.000 53.536 63.721 0.781 461.000 52.408 63.384 0.768 455.000 41.454 61.141 0.754 456.000 38.271 59.231 0.754 517.000 35.306 63.472 0.754 525.000 26.414 49.214 0.779 523.000 31.917 55.816 0.799 519.000 38.030 61.713 0.780 509.000 27.534 48.664 0.769 512.000 18.387 45.351 0.801 519.000 50.556 57.888 0.792 517.000 43.901 54.091 0.852 510.000 48.572 59.098 0.807 509.000 43.899 58.962 0.797 501.000 37.532 55.433 0.783 507.000 40.357 60.403 0.779 569.000 35.489 60.721 0.785 580.000 29.027 48.440 0.817 578.000 34.485 57.981 0.810 565.000 42.598 60.258 0.798 547.000 30.306 47.312 0.795 555.000 26.451 46.980 0.785 562.000 47.460 54.846 0.785 561.000 50.104 56.824 0.785 555.000 61.465 67.744 0.805 544.000 53.726 62.849 0.824 537.000 39.477 54.691 0.819 543.000 43.895 65.461 0.827 594.000 31.481 53.724 0.826 611.000 29.896 54.560 0.829 613.000 33.842 57.722 0.830 611.000 39.120 55.458 0.825 594.000 33.702 48.490 0.817 595.000 25.094 46.362
Names of X columns:
1 2 3 4
Method
ward
single
complete
average
mcquitty
median
centroid
# of (top) clusters to display
ALL
2
3
4
5
6
7
8
9
10
15
20
Horizontal
FALSE
TRUE
Triangle
FALSE
TRUE
Chart options
Title:
Label y-axis:
Label x-axis:
R Code
par3 <- as.logical(par3) par4 <- as.logical(par4) if (par3 == 'TRUE'){ dum = xlab xlab = ylab ylab = dum } x <- t(y) hc <- hclust(dist(x),method=par1) d <- as.dendrogram(hc) str(d) mysub <- paste('Method: ',par1) bitmap(file='test1.png') if (par4 == 'TRUE'){ plot(d,main=main,ylab=ylab,xlab=xlab,horiz=par3, nodePar=list(pch = c(1,NA), cex=0.8, lab.cex = 0.8),type='t',center=T, sub=mysub) } else { plot(d,main=main,ylab=ylab,xlab=xlab,horiz=par3, nodePar=list(pch = c(1,NA), cex=0.8, lab.cex = 0.8), sub=mysub) } dev.off() if (par2 != 'ALL'){ if (par3 == 'TRUE'){ ylab = 'cluster' } else { xlab = 'cluster' } par2 <- as.numeric(par2) memb <- cutree(hc, k = par2) cent <- NULL for(k in 1:par2){ cent <- rbind(cent, colMeans(x[memb == k, , drop = FALSE])) } hc1 <- hclust(dist(cent),method=par1, members = table(memb)) de <- as.dendrogram(hc1) bitmap(file='test2.png') if (par4 == 'TRUE'){ plot(de,main=main,ylab=ylab,xlab=xlab,horiz=par3, nodePar=list(pch = c(1,NA), cex=0.8, lab.cex = 0.8),type='t',center=T, sub=mysub) } else { plot(de,main=main,ylab=ylab,xlab=xlab,horiz=par3, nodePar=list(pch = c(1,NA), cex=0.8, lab.cex = 0.8), sub=mysub) } dev.off() str(de) } load(file='createtable') a<-table.start() a<-table.row.start(a) a<-table.element(a,'Summary of Dendrogram',2,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Label',header=TRUE) a<-table.element(a,'Height',header=TRUE) a<-table.row.end(a) num <- length(x[,1])-1 for (i in 1:num) { a<-table.row.start(a) a<-table.element(a,hc$labels[i]) a<-table.element(a,hc$height[i]) a<-table.row.end(a) } a<-table.end(a) table.save(a,file='mytable1.tab') if (par2 != 'ALL'){ a<-table.start() a<-table.row.start(a) a<-table.element(a,'Summary of Cut Dendrogram',2,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Label',header=TRUE) a<-table.element(a,'Height',header=TRUE) a<-table.row.end(a) num <- par2-1 for (i in 1:num) { a<-table.row.start(a) a<-table.element(a,i) a<-table.element(a,hc1$height[i]) a<-table.row.end(a) } a<-table.end(a) table.save(a,file='mytable2.tab') }
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R Server
Big Analytics Cloud Computing Center
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