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Data X:
569 117.8 77.9 85.7 580 113.5 60 61.9 578 121.2 99.5 104.9 565 130.4 95 107.9 547 115.2 105.6 95.6 555 117.9 102.5 79.8 562 110.7 93.3 94.8 561 107.6 97.3 93.7 555 124.3 127 108.1 544 115.1 111.7 96.9 537 112.5 96.4 88.8 543 127.9 133 106.7 594 117.4 72.2 86.8 611 119.3 95.8 69.8 613 130.4 124.1 110.9 611 126 127.6 105.4 594 125.4 110.7 99.2 595 130.5 104.6 84.4 591 115.9 112.7 87.2 589 108.7 115.3 91.9 584 124 139.4 97.9 573 119.4 119 94.5 567 118.6 97.4 85 569 131.3 154 100.3 621 111.1 81.5 78.7 629 124.8 88.8 65.8 628 132.3 127.7 104.8 612 126.7 105.1 96 595 131.7 114.9 103.3 597 130.9 106.4 82.9 593 122.1 104.5 91.4 590 113.2 121.6 94.5 580 133.6 141.4 109.3 574 119.2 99 92.1 573 129.4 126.7 99.3 573 131.4 134.1 109.6 620 117.1 81.3 87.5 626 130.5 88.6 73.1 620 132.3 132.7 110.7 588 140.8 132.9 111.6 566 137.5 134.4 110.7 557 128.6 103.7 84 561 126.7 119.7 101.6 549 120.8 115 102.1 532 139.3 132.9 113.9 526 128.6 108.5 99 511 131.3 113.9 100.4 499 136.3 142 109.5 555 128.8 97.7 93.1 565 133.2 92.2 77 542 136.3 128.8 108 527 151.1 134.9 119.9 510 145 128.2 105.9 514 134.4 114.8 78.2 517 135.7 117.9 100.3 508 128.7 119.1 102.2 493 129.2 120.7 97 490 138.6 129.1 101.3 469 132.7 117.6 89.2 478 132.5 129.2 93.3 528 135.2 99.1 86.4
Names of X columns:
werkloosheid voeding_dranken automobiel textiel
Method
ward
ward
single
complete
average
mcquitty
median
centroid
# of (top) clusters to display
ALL
ALL
2
3
4
5
6
7
8
9
10
15
20
Horizontal
FALSE
FALSE
TRUE
Triangle
FALSE
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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1 seconds
R Server
Big Analytics Cloud Computing Center
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