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Data X:
88900 124.9 87280 132 85519 151.4 83647 108.9 81616 121.3 80100 123.4 94027 90.3 102327 79.3 104296 117.2 101593 116.9 94816 120.8 93535 96.1 93618 100.8 92330 105.3 90751 116.1 88576 112.8 86102 114.5 85494 117.2 103432 77.1 108870 80.1 109713 120.3 106960 133.4 103195 109.4 102348 93.2 102158 91.2 100431 99.2 97649 108.2 95611 101.5 93035 106.9 93579 104.4 111777 77.9 116065 60 116609 99.5 112934 95 107660 105.6 107965 102.5 107772 93.3 106201 97.3 102288 127 99217 111.7 96511 96.4 96456 133 113021 72.2 117836 95.8 118492 124.1 113922 127.6 109317 110.7 107496 104.6 105524 112.7 103824 115.3 101833 139.4 99436 119 96915 97.4 96072 154 111941 81.5 116008 88.8 117557 127.7 113445 105.1 108762 114.9 106661 106.4 102824 104.5 101912 121.6 99005 141.4 97894 99 96256 126.7 95606 134.1 108948 81.3 111223 88.6 113142 132.7 106078 132.9 100992 134.4 97413 103.7
Names of X columns:
werkl50 prodtransp
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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