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Data X:
116.1 117.1 118.9 100.3 102.5 107.0 108.8 97.6 102.0 107.0 115.6 89.1 101.3 111.0 95.0 99.1 100.6 108.2 92.8 94.9 100.9 96.3 108.9 96.5 104.2 100.9 109.8 92.6 108.3 107.7 106.1 80.8 108.9 106.2 102.8 89.5 109.9 118.7 98.4 101.4 106.8 116.1 85.7 95.9 112.7 118.1 114.6 92.3 113.4 118.4 129.4 91.2 101.3 110.8 117.7 88.3 97.8 106.4 126.6 80.7 95.0 112.2 103.8 89.9 93.8 108.3 101.5 87.2 94.5 96.0 118.7 86.9 101.4 100.6 119.6 82.8 105.8 107.8 114.8 72.6 106.6 108.4 109.9 81.3 109.7 120.9 106.3 91.2 108.8 117.3 95.0 87.3 113.4 119.7 124.5 83.4 113.7 119.6 140.4 81.7 103.6 111.8 128.8 80.2 98.2 108.1 137.5 74.1 95.5 111.8 113.3 80.6 94.4 105.5 110.3 79.0 95.9 93.6 129.1 79.3 103.2 103.9 128.4 71.2 104.1 100.3 120.3 78.1 127.6 106.6 113.6 68.2 130.3 118.4 96.9 81.0 133.0 106.6 124.7 106.9 140.4 109.8 126.4 123.7 123.5 115.9 131.9 73.7 116.9 111.7 122.5 69.2 115.9 119.8 113.1 72.5 113.1 116.1 99.8 75.7 112.1 103.2 116.0 73.5 112.4 99.0 115.0 70.4 118.9 112.3 114.0 65.7 117.4 104.2 111.0 68.1 115.6 114.0 91.7 62.4 120.7 121.7 90.6 64.7 114.9 107.2 103.3 77.7 122.0 112.8 106.7 85.9 119.6 117.8 111.2 61.0 114.6 113.3 102.9 57.4 118.4 116.1 126.5 75.1 110.9 111.8 115.1 75.9 111.6 110.2 110.2 71.8 114.6 110.0 110.1 72.3 112.1 102.9 103.3 67.3 117.4 110.1 107.7 71.5 114.8 102.7 103.9 67.6 123.4 118.7 114.0 74.2 118.1 109.0 117.2 77.6 121.9 115.7 117.0 76.4 123.3 118.1 116.5 74.2
Names of X columns:
Belgie Vlaanderen Wallonie Brussel
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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Computing time
1 seconds
R Server
Big Analytics Cloud Computing Center
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