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Data X:
641 12055 2411 550 12113 2361 542 9617 1924 629 12646 2487 687 13581 2675 612 12162 2296 588 10970 2102 567 11880 2322 564 11888 2274 570 12927 2501 635 12300 2435 591 12093 2273 634 12381 2455 576 12197 2329 352 9455 1897 508 13168 2608 586 13428 2712 666 11981 2322 694 11885 2283 651 11692 2241 655 12234 2417 734 14341 2829 648 13131 2601 678 12421 2321 816 14286 2769 591 12865 2457 564 11160 2143 743 14316 2764 694 14389 2789 729 14014 2680 749 13419 2537 539 12770 2683 569 13316 2700 693 15333 3098 581 14243 3015 507 13824 2878 613 14963 3011 443 13203 2612 523 12199 2419 597 15509 3097 534 14200 3013 523 15170 3397 559 14058 3423 431 13786 3299 538 14148 3066 612 16542 3918 428 13588 3154 522 15582 3335 531 15803 3462 426 14131 3019 410 12923 2832 551 15612 3301 556 16034 3343 460 16037 3464 289 14038 3017 392 15331 3201 401 15038 3135 399 17402 3550 355 14993 3247 338 16044 3442 379 16930 3536 334 15921 3385 322 14417 2997 450 15961 3403 486 17852 3900 422 16484 3776 406 14216 3198 420 17430 4022 432 17840 3845 418 17629 3818
Names of X columns:
Brussels Vlaams Waals
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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Computing time
1 seconds
R Server
Big Analytics Cloud Computing Center
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