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Data X:
110.7 101.2 123.9 113.1 100.5 124.9 99.6 98 112.7 93.6 106.6 121.9 98.6 90.1 100.6 99.6 96.9 104.3 114.3 125.9 120.4 107.8 112 107.5 101.2 100 102.9 112.5 123.9 125.6 100.5 79.8 107.5 93.9 83.4 108.8 116.2 113.6 128.4 112 112.9 121.1 106.4 104 119.5 95.7 109.9 128.7 96 99 108.7 95.8 106.3 105.5 103 128.9 119.8 102.2 111.1 111.3 98.4 102.9 110.6 111.4 130 120.1 86.6 87 97.5 91.3 87.5 107.7 107.9 117.6 127.3 101.8 103.4 117.2 104.4 110.8 119.8 93.4 112.6 116.2 100.1 102.5 111 98.5 112.4 112.4 112.9 135.6 130.6 101.4 105.1 109.1 107.1 127.7 118.8 110.8 137 123.9 90.3 91 101.6 95.5 90.5 112.8 111.4 122.4 128 113 123.3 129.6 107.5 124.3 125.8 95.9 120 119.5 106.3 118.1 115.7 105.2 119 113.6 117.2 142.7 129.7 106.9 123.6 112 108.2 129.6 116.8 113 151.6 127 97.2 110.4 112.1 99.9 99.2 114.2 108.1 130.5 121.1 118.1 136.2 131.6 109.1 129.7 125 93.3 128 120.4 112.1 121.6 117.7 111.8 135.8 117.5 112.5 143.8 120.6 116.3 147.5 127.5 110.3 136.2 112.3 117.1 156.6 124.5 103.4 123.3 115.2 96.2 100.4 105.4
Names of X columns:
Intermediaire_goederen Investeringsgoederen Consumptiegoederen
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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Big Analytics Cloud Computing Center
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