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Data X:
100.70 101.30 97.90 97.60 96.50 96.40 96.60 97.00 96.60 96.40 95.50 94.70 91.80 89.30 89.30 85.90 87.00 83.30 85.90 81.50 88.00 85.00 87.90 84.80 89.20 87.50 90.90 89.00 91.60 90.00 90.20 89.60 89.10 87.40 87.50 84.80 86.30 81.90 86.00 81.10 84.40 79.10 86.10 80.50 91.00 88.50 92.70 90.90 88.00 84.90 84.30 80.00 82.20 76.50 80.80 75.40 79.40 73.50 80.20 74.30 82.20 77.70 82.20 77.90 81.20 76.70 82.10 77.20 88.10 86.00 88.50 86.90 92.10 92.00 98.60 101.70 100.90 104.50 100.60 101.70 101.10 100.60 102.10 100.30 103.60 102.50 102.80 101.00 108.30 108.60 104.00 103.40 106.10 106.40 106.30 106.60 109.00 108.90 111.00 110.50 113.70 114.00 112.70 112.80 110.30 109.60 114.50 116.00 119.30 124.60 121.80 129.00 125.40 131.50 129.70 138.60 129.40 138.10 134.50 146.30 141.20 157.60 141.40 158.40 152.20 176.30 167.70 199.90 173.30 210.40 168.70 202.60 172.60 207.10 169.80 202.00 172.00 203.40 179.40 216.30 174.60 207.30 172.50 203.50 172.60 204.40 176.30 203.70 178.90 205.70 179.60 208.00 179.90 209.30 180.30 208.70 180.90 206.50 177.70 204.50
Names of X columns:
Metaal Non-ferro
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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