Send output to:
Browser Blue - Charts White
Browser Black/White
CSV
Data X:
0.9383 90.8 15 467.037 0.9217 96.4 3 460.070 0.9095 90 2 447.988 0.892 92.1 -2 442.867 0.8742 97.2 1 436.087 0.8532 95.1 1 431.328 0.8607 88.5 -1 484.015 0.9005 91 -6 509.673 0.9111 90.5 -13 512.927 0.9059 75 -25 502.831 0.8883 66.3 -26 470.984 0.8924 66 -9 471.067 0.8833 68.4 1 476.049 0.87 70.6 3 474.605 0.8758 83.9 6 470.439 0.8858 90.1 2 461.251 0.917 90.6 5 454.724 0.9554 87.1 5 455.626 0.9922 90.8 0 516.847 0.9778 94.1 -5 525.192 0.9808 99.8 -4 522.975 0.9811 96.8 -2 518.585 1.0014 87 -1 509.239 1.0183 96.3 -8 512.238 1.0622 107.1 -16 519.164 1.0773 115.2 -19 517.009 1.0807 106.1 -28 509.933 1.0848 89.5 -11 509.127 1.1582 91.3 -4 500.857 1.1663 97.6 -9 506.971 1.1372 100.7 -12 569.323 1.1139 104.6 -10 579.714 1.1222 94.7 -2 577.992 1.1692 101.8 -13 565.464 1.1702 102.5 0 547.344 1.2286 105.3 0 554.788 1.2613 110.3 4 562.325 1.2646 109.8 7 560.854 1.2262 117.3 5 555.332 1.1985 118.8 2 543.599 1.2007 131.3 -2 536.662 1.2138 125.9 6 542.722 1.2266 133.1 -3 593.530 1.2176 147 1 610.763 1.2218 145.8 0 612.613 1.249 164.4 -7 611.324 1.2991 149.8 -6 594.167 1.3408 137.7 -4 595.454 1.3119 151.7 -4 590.865 1.3014 156.8 -2 589.379 1.3201 180 2 584.428 1.2938 180.4 -5 573.100 1.2694 170.4 -15 567.456 1.2165 191.6 -16 569.028 1.2037 199.5 -18 620.735 1.2292 218.2 -13 628.884 1.2256 217.5 -23 628.232 1.2015 205 -10 612.117 1.1786 194 -10 595.404 1.1856 199.3 -6 597.141 1.2103 219.3 -3 593.408 1.1938 211.1 -4 590.072 1.202 215.2 -7 579.799 1.2271 240.2 -7 574.205 1.277 242.2 -7 572.775 1.265 240.7 -3 572.942 1.2684 255.4 0 619.567 1.2811 253 -5 625.809 1.2727 218.2 -3 619.916 1.2611 203.7 3 587.625 1.2881 205.6 2 565.742 1.3213 215.6 -7 557.274
Names of X columns:
$ RA CV WH
Method
ward
single
complete
average
mcquitty
median
centroid
# of (top) clusters to display
ALL
2
3
4
5
6
7
8
9
10
15
20
Horizontal
FALSE
TRUE
Triangle
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