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Data X:
110.40 109.20 99.90 72.50 96.40 88.60 99.80 59.40 101.90 94.30 99.80 85.70 106.20 98.30 100.30 88.20 81.00 86.40 99.90 62.80 94.70 80.60 99.90 87.00 101.00 104.10 100.00 79.20 109.40 108.20 100.10 112.00 102.30 93.40 100.10 79.20 90.70 71.90 100.20 132.10 96.20 94.10 100.30 40.10 96.10 94.90 100.60 69.00 106.00 96.40 100.00 59.40 103.10 91.10 100.10 73.80 102.00 84.40 100.20 57.40 104.70 86.40 100.00 81.10 86.00 88.00 100.10 46.60 92.10 75.10 100.10 41.40 106.90 109.70 100.10 71.20 112.60 103.00 100.50 67.90 101.70 82.10 100.50 72.00 92.00 68.00 100.50 145.50 97.40 96.40 96.30 39.70 97.00 94.30 96.30 51.90 105.40 90.00 96.80 73.70 102.70 88.00 96.80 70.90 98.10 76.10 96.90 60.80 104.50 82.50 96.80 61.00 87.40 81.40 96.80 54.50 89.90 66.50 96.80 39.10 109.80 97.20 96.80 66.60 111.70 94.10 97.00 58.50 98.60 80.70 97.00 59.80 96.90 70.50 97.00 80.90 95.10 87.80 96.80 37.30 97.00 89.50 96.90 44.60 112.70 99.60 97.20 48.70 102.90 84.20 97.30 54.00 97.40 75.10 97.30 49.50 111.40 92.00 97.20 61.60 87.40 80.80 97.30 35.00 96.80 73.10 97.30 35.70 114.10 99.80 97.30 51.30 110.30 90.00 97.30 49.00 103.90 83.10 97.30 41.50 101.60 72.40 97.30 72.50 94.60 78.80 98.10 42.10 95.90 87.30 96.80 44.10 104.70 91.00 96.80 45.10 102.80 80.10 96.80 50.30 98.10 73.60 96.80 40.90 113.90 86.40 96.80 47.20 80.90 74.50 96.80 36.90 95.70 71.20 96.80 40.90 113.20 92.40 96.80 38.30 105.90 81.50 96.80 46.30 108.80 85.30 96.80 28.40 102.30 69.90 96.80 78.40 99.00 84.20 96.90 36.80 100.70 90.70 97.10 50.70 115.50 79.34 97.10 42.80
Names of X columns:
Totaal Kleding Prijs Investering
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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