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Data X:
106.9 108.8 85.3 112.6 113.2 73.8 101.7 105.5 55.2 92 77.8 54.4 97.4 102.1 80.8 97 97 88 105.4 95.5 74.5 102.7 99.3 55.1 98.1 86.4 47.2 104.5 92.4 54.2 87.4 85.7 70.6 89.9 61.9 78.5 109.8 104.9 77.1 111.7 107.9 56.6 98.6 95.6 39.8 96.9 79.8 44.1 95.1 94.8 66.9 97 93.7 75.3 112.7 108.1 74.9 102.9 96.9 48.8 97.4 88.8 37 111.4 106.7 49.8 87.4 86.8 63.2 96.8 69.8 75.9 114.1 110.9 68.5 110.3 105.4 49.2 103.9 99.2 40.3 101.6 84.4 38.6 94.6 87.2 54.2 95.9 91.9 70.6 104.7 97.9 68 102.8 94.5 43 98.1 85 42.3 113.9 100.3 47.7 80.9 78.7 57.7 95.7 65.8 75.8 113.2 104.8 57.2 105.9 96 43.6 108.8 103.3 40 102.3 82.9 35.9 99 91.4 59.5 100.7 94.5 72.7 115.5 109.3 70.9 100.7 92.1 44.9 109.9 99.3 44.5 114.6 109.6 48 85.4 87.5 60.4 100.5 73.1 71.8 114.8 110.7 63.2 116.5 111.6 32.4 112.9 110.7 33.9 102 84 24.2 106 101.6 64.7 105.3 102.1 73 118.8 113.9 61.7 106.1 99 31.9 109.3 100.4 30.8 114.3 111.1 34.1 91.9 93 47.4 104.4 74.1 53
Names of X columns:
Industrie Textiel Kleding&Bont
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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