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Data X:
7 30 991 4.286 1.604 33.033 20.435 1.565 0.902 4.727 8 37 788 4.625 1.685 21.297 8.611 1.735 1.079 5.192 25 119 2632 4.76 3.345 22.118 10.053 1.478 0.852 4.581 6 62 1773 10.333 2.944 28.597 15.523 1.513 0.912 4.451 8 61 1767 7.625 3.462 28.967 15.004 1.654 0.993 4.921 7 67 1754 9.571 4.353 26.179 12.135 1.609 0.906 4.876 6 62 1708 10.333 3.983 27.548 14.77 1.441 0.804 4.33 10 58 1653 5.8 2.44 28.5 18.083 1.469 0.737 4.191 19 118 2401 6.211 2.347 20.347 11.097 1.549 0.872 4.641 5 44 1175 8.8 5.805 26.705 13.401 1.641 0.995 4.879 13 92 2112 7.077 3.402 22.957 9.432 1.73 1.151 5.076 12 71 2032 5.917 2.778 28.62 13.036 1.688 0.992 5.124 8 49 1455 6.125 2.357 29.694 10.243 1.713 1.056 5.034 8 49 1609 6.125 3.044 32.837 16.54 1.608 0.962 4.817 14 80 1792 5.714 2.128 22.4 8.847 1.852 1.097 5.523 9 64 1562 7.111 3.723 24.406 10.212 1.761 1.089 5.257 17 111 2380 6.529 3.105 21.441 9.93 1.719 1.06 5.072 5 81 1910 16.2 6.496 23.58 10.038 1.564 0.986 4.815 10 85 1663 8.5 4.994 19.565 6.856 1.696 0.952 5.084 7 58 1312 8.286 3.946 22.621 9.994 1.745 1.102 5.096 4 20 473 5 2.16 23.65 9.453 1.753 1.064 5.321 9 66 1584 7.333 5.701 24 10.319 1.872 1.269 5.528
Names of X columns:
DESPC 'Paragraph count, number of paragraphs' DESSC 'Sentence count, number of sentences' DESWC 'Word count, number of words' DESPL 'Paragraph length, number of sentences in a paragraph, mean' DESPLd 'Paragraph length, number of sentences in a pragraph, standard deviation' DESSL 'Sentence length, number of words, mean' DESSLd 'Sentence length, number of words, standard deviation' DESWLsy 'Word length, number of syllables, mean' DESWLsyd 'Word length, number of syllables, standard deviation' DESWLlt 'Word length, number of letters, mean' DESWLltd 'Word length, number of letters, standard deviation'
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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R Server
Big Analytics Cloud Computing Center
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