Send output to:
Browser Blue - Charts White
Browser Black/White
CSV
Data X:
70.9 58.4 73 56.8 83.9 69.4 73.2 59.6 76.7 63.6 83.1 68.4 59.8 55.9 68.2 59.1 91.1 66.2 85 66.5 81.6 64.5 78.8 74.5 73 60 74.3 61.4 81.2 70.1 79.9 65.7 79.7 67.1 83.6 70.8 68.6 61.5 666 60.1 83.5 70.1 91.8 73.2 80.5 67.1 84.7 77.4 78.7 66.9 78.4 66 83.1 74 84.8 75.8 80.7 72.2 91.8 78.2 75.3 71.4 71.8 66.3 93 79.9 94.3 81.2 83.7 72.2 95.6 88.4 82.2 72.2 83.4 73 93.1 83.8 88.7 79.7 84.5 79.1 95 84.3 76.6 76.8 73.4 69.3 93 81.3 91 80.9 85.3 76 89.5 90 76.1 72.6 76.1 73.9 91.5 91.2 85.4 83.1 80 80.1 94 91.1 72.6 80.1 80.8 76.3 94.1 93.2 94.9 91.6 91.9 88.5 99.2 103.2 84.7 84.9 93.7 89 106.7 106.9 93.5 91.4 104.8 99.6 103.5 100.6 83.1 88 89.6 89.7 105.7 106.7 110.7 106 110.4 104.4 109 123.7 106 97.1 100.9 95.5 114.3 112.2 101.2 101.4 109.2 106.9 111.6 109.5 91.7 96.4 93.7 93.9 105.7 104.2 109.5 109.2 105.3 108.9 102.8 117.9 100.6 98.2 97.6 101.4 110.3 111.6 107.2 113.6 107.2 110.8 108.1 113.9 97.1 105.5 92.2 95.9 112.2 115.8 111.6 119.9 115.7 107.3 111.3 126.9 104.2 107.8 103.2 105.5 112.7 120.2 106.4 116 102.6 110.4 110.6 120.8 95.2 110.7 89 99.9 112.5 126.8 116.8 128.6 107.2 112.9 113.6 136.6 101.8 113.3 102.6 116.3 122.7 137.5 110.3 126.7 110.5 118.5 121.6 136.4 100.3 120.2 100.7 117.2 123.4 133.3 127.1 134.8 124.1 129.9 131.2 149.5 111.6 118.5 114.2 122.8 130.1 145.7 125.9 133.6 119 130.8 133.8 146.8 107.5 126 113.5 124.4 134.4 145.5 126.8 146.3 135.6 145 139.9 162 129.8 132.2 131 140.2 153.1 164.8 134.1 143.7 144.1 144.2
Names of X columns:
Totaal Niet-Industrieel
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') }
Compute
Summary of computational transaction
Raw Input
view raw input (R code)
Raw Output
view raw output of R engine
Computing time
0 seconds
R Server
Big Analytics Cloud Computing Center
Click here to blog (archive) this computation