R version 2.12.1 (2010-12-16) Copyright (C) 2010 The R Foundation for Statistical Computing ISBN 3-900051-07-0 Platform: i486-pc-linux-gnu (32-bit) R is free software and comes with ABSOLUTELY NO WARRANTY. You are welcome to redistribute it under certain conditions. Type 'license()' or 'licence()' for distribution details. R is a collaborative project with many contributors. Type 'contributors()' for more information and 'citation()' on how to cite R or R packages in publications. Type 'demo()' for some demos, 'help()' for on-line help, or 'help.start()' for an HTML browser interface to help. Type 'q()' to quit R. > x <- array(list(1 + ,78 + ,20 + ,17 + ,30 + ,28 + ,2 + ,46 + ,38 + ,17 + ,42 + ,39 + ,3 + ,18 + ,0 + ,0 + ,0 + ,0 + ,4 + ,84 + ,49 + ,22 + ,54 + ,54 + ,5 + ,125 + ,74 + ,30 + ,86 + ,80 + ,6 + ,215 + ,104 + ,31 + ,157 + ,144 + ,7 + ,50 + ,37 + ,19 + ,36 + ,36 + ,8 + ,48 + ,53 + ,25 + ,48 + ,48 + ,9 + ,37 + ,42 + ,30 + ,45 + ,42 + ,10 + ,86 + ,62 + ,26 + ,77 + ,71 + ,11 + ,69 + ,50 + ,20 + ,49 + ,49 + ,12 + ,59 + ,65 + ,25 + ,77 + ,74 + ,13 + ,85 + ,28 + ,15 + ,28 + ,27 + ,14 + ,84 + ,48 + ,22 + ,84 + ,83 + ,15 + ,44 + ,42 + ,12 + ,31 + ,31 + ,16 + ,67 + ,47 + ,19 + ,28 + ,28 + ,17 + ,49 + ,71 + ,28 + ,99 + ,98 + ,18 + ,47 + ,0 + ,12 + ,2 + ,2 + ,19 + ,77 + ,50 + ,28 + ,41 + ,43 + ,20 + ,20 + ,12 + ,13 + ,25 + ,24 + ,21 + ,49 + ,16 + ,14 + ,16 + ,16 + ,22 + ,81 + ,76 + ,27 + ,96 + ,95 + ,23 + ,58 + ,29 + ,25 + ,23 + ,22 + ,24 + ,45 + ,38 + ,30 + ,33 + ,33 + ,25 + ,73 + ,50 + ,18 + ,46 + ,45 + ,26 + ,22 + ,33 + ,17 + ,59 + ,59 + ,27 + ,138 + ,45 + ,22 + ,72 + ,66 + 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+ ,17 + ,33 + ,33 + ,112 + ,35 + ,41 + ,18 + ,44 + ,41 + ,113 + ,47 + ,45 + ,21 + ,56 + ,57 + ,114 + ,55 + ,29 + ,17 + ,49 + ,49 + ,115 + ,5 + ,0 + ,0 + ,0 + ,0 + ,116 + ,0 + ,0 + ,0 + ,0 + ,0 + ,117 + ,37 + ,32 + ,20 + ,45 + ,45 + ,118 + ,65 + ,58 + ,26 + ,78 + ,78 + ,119 + ,81 + ,17 + ,26 + ,51 + ,46 + ,120 + ,32 + ,24 + ,20 + ,25 + ,25 + ,121 + ,19 + ,7 + ,1 + ,1 + ,1 + ,122 + ,58 + ,62 + ,24 + ,62 + ,59 + ,123 + ,33 + ,30 + ,14 + ,29 + ,29 + ,124 + ,42 + ,49 + ,26 + ,26 + ,26 + ,125 + ,37 + ,3 + ,12 + ,4 + ,4 + ,126 + ,12 + ,10 + ,2 + ,10 + ,10 + ,127 + ,41 + ,42 + ,16 + ,43 + ,43 + ,128 + ,23 + ,18 + ,22 + ,36 + ,36 + ,129 + ,35 + ,40 + ,28 + ,43 + ,41 + ,130 + ,9 + ,1 + ,2 + ,0 + ,0 + ,131 + ,9 + ,0 + ,0 + ,0 + ,0 + ,132 + ,49 + ,29 + ,17 + ,33 + ,32 + ,133 + ,3 + ,0 + ,1 + ,0 + ,0 + ,134 + ,41 + ,46 + ,17 + ,53 + ,53 + ,135 + ,3 + ,5 + ,0 + ,0 + ,0 + ,136 + ,16 + ,8 + ,4 + ,6 + ,6 + ,137 + ,0 + ,0 + ,0 + ,0 + ,0 + ,138 + ,41 + ,21 + ,25 + ,19 + ,18 + ,139 + ,31 + ,21 + ,26 + ,26 + ,26 + ,140 + ,4 + ,0 + ,0 + ,0 + ,0 + ,141 + ,11 + ,0 + ,0 + ,0 + ,0 + ,142 + ,20 + ,15 + ,15 + ,16 + ,16 + ,143 + ,40 + ,40 + ,18 + ,84 + ,84 + ,144 + ,16 + ,17 + ,19 + ,28 + ,22) + ,dim=c(6 + ,144) + ,dimnames=list(c('Ranking' + ,'Logins' + ,'BloggedComputations' + ,'ReviewedCompendiums' + ,'includedhyperlinks' + ,'includedblogs') + ,1:144)) > y <- array(NA,dim=c(6,144),dimnames=list(c('Ranking','Logins','BloggedComputations','ReviewedCompendiums','includedhyperlinks','includedblogs'),1:144)) > for (i in 1:dim(x)[1]) + { + for (j in 1:dim(x)[2]) + { + y[i,j] <- as.numeric(x[i,j]) + } + } > par4 = 'yes' > par3 = '2' > par2 = 'quantiles' > par1 = '5' > library(party) Loading required package: survival Loading required package: splines Loading required package: grid Loading required package: modeltools Loading required package: stats4 Loading required package: coin Loading required package: mvtnorm Loading required package: zoo Loading required package: sandwich Loading required package: strucchange Loading required package: vcd Loading required package: MASS Loading required package: colorspace > library(Hmisc) Attaching package: 'Hmisc' The following object(s) are masked from 'package:survival': untangle.specials The following object(s) are masked from 'package:base': format.pval, round.POSIXt, trunc.POSIXt, units > par1 <- as.numeric(par1) > par3 <- as.numeric(par3) > x <- data.frame(t(y)) > is.data.frame(x) [1] TRUE > x <- x[!is.na(x[,par1]),] > k <- length(x[1,]) > n <- length(x[,1]) > colnames(x)[par1] [1] "includedhyperlinks" > x[,par1] [1] 30 42 0 54 86 157 36 48 45 77 49 77 28 84 31 28 99 2 [19] 41 25 16 96 23 33 46 59 72 72 62 55 27 41 51 26 65 0 [37] 28 44 36 100 104 35 69 73 106 53 43 49 38 51 14 40 79 52 [55] 44 34 47 32 31 40 42 34 40 35 11 43 53 82 41 6 82 47 [73] 108 46 38 0 45 57 20 56 38 42 37 36 34 53 85 36 33 57 [91] 50 71 32 45 33 53 64 14 38 39 8 38 24 22 18 3 49 5 [109] 0 47 33 44 56 49 0 0 45 78 51 25 1 62 29 26 4 10 [127] 43 36 43 0 0 33 0 53 0 6 0 19 26 0 0 16 84 28 > if (par2 == 'kmeans') { + cl <- kmeans(x[,par1], par3) + print(cl) + clm <- matrix(cbind(cl$centers,1:par3),ncol=2) + clm <- clm[sort.list(clm[,1]),] + for (i in 1:par3) { + cl$cluster[cl$cluster==clm[i,2]] <- paste('C',i,sep='') + } + cl$cluster <- as.factor(cl$cluster) + print(cl$cluster) + x[,par1] <- cl$cluster + } > if (par2 == 'quantiles') { + x[,par1] <- cut2(x[,par1],g=par3) + } > if (par2 == 'hclust') { + hc <- hclust(dist(x[,par1])^2, 'cen') + print(hc) + memb <- cutree(hc, k = par3) + dum <- c(mean(x[memb==1,par1])) + for (i in 2:par3) { + dum <- c(dum, mean(x[memb==i,par1])) + } + hcm <- matrix(cbind(dum,1:par3),ncol=2) + hcm <- hcm[sort.list(hcm[,1]),] + for (i in 1:par3) { + memb[memb==hcm[i,2]] <- paste('C',i,sep='') + } + memb <- as.factor(memb) + print(memb) + x[,par1] <- memb + } > if (par2=='equal') { + ed <- cut(as.numeric(x[,par1]),par3,labels=paste('C',1:par3,sep='')) + x[,par1] <- as.factor(ed) + } > table(x[,par1]) [ 0, 41) [41,157] 74 70 > colnames(x) [1] "Ranking" "Logins" "BloggedComputations" [4] "ReviewedCompendiums" "includedhyperlinks" "includedblogs" > colnames(x)[par1] [1] "includedhyperlinks" > x[,par1] [1] [ 0, 41) [41,157] [ 0, 41) [41,157] [41,157] [41,157] [ 0, 41) [41,157] [9] [41,157] [41,157] [41,157] [41,157] [ 0, 41) [41,157] [ 0, 41) [ 0, 41) [17] [41,157] [ 0, 41) [41,157] [ 0, 41) [ 0, 41) [41,157] [ 0, 41) [ 0, 41) [25] [41,157] [41,157] [41,157] [41,157] [41,157] [41,157] [ 0, 41) [41,157] [33] [41,157] [ 0, 41) [41,157] [ 0, 41) [ 0, 41) [41,157] [ 0, 41) [41,157] [41] [41,157] [ 0, 41) [41,157] [41,157] [41,157] [41,157] [41,157] [41,157] [49] [ 0, 41) [41,157] [ 0, 41) [ 0, 41) [41,157] [41,157] [41,157] [ 0, 41) [57] [41,157] [ 0, 41) [ 0, 41) [ 0, 41) [41,157] [ 0, 41) [ 0, 41) [ 0, 41) [65] [ 0, 41) [41,157] [41,157] [41,157] [41,157] [ 0, 41) [41,157] [41,157] [73] [41,157] [41,157] [ 0, 41) [ 0, 41) [41,157] [41,157] [ 0, 41) [41,157] [81] [ 0, 41) [41,157] [ 0, 41) [ 0, 41) [ 0, 41) [41,157] [41,157] [ 0, 41) [89] [ 0, 41) [41,157] [41,157] [41,157] [ 0, 41) [41,157] [ 0, 41) [41,157] [97] [41,157] [ 0, 41) [ 0, 41) [ 0, 41) [ 0, 41) [ 0, 41) [ 0, 41) [ 0, 41) [105] [ 0, 41) [ 0, 41) [41,157] [ 0, 41) [ 0, 41) [41,157] [ 0, 41) [41,157] [113] [41,157] [41,157] [ 0, 41) [ 0, 41) [41,157] [41,157] [41,157] [ 0, 41) [121] [ 0, 41) [41,157] [ 0, 41) [ 0, 41) [ 0, 41) [ 0, 41) [41,157] [ 0, 41) [129] [41,157] [ 0, 41) [ 0, 41) [ 0, 41) [ 0, 41) [41,157] [ 0, 41) [ 0, 41) [137] [ 0, 41) [ 0, 41) [ 0, 41) [ 0, 41) [ 0, 41) [ 0, 41) [41,157] [ 0, 41) Levels: [ 0, 41) [41,157] > if (par2 == 'none') { + m <- ctree(as.formula(paste(colnames(x)[par1],' ~ .',sep='')),data = x) + } > > #Note: the /var/www/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/www/rcomp/createtable") > > if (par2 != 'none') { + m <- ctree(as.formula(paste('as.factor(',colnames(x)[par1],') ~ .',sep='')),data = x) + if (par4=='yes') { + a<-table.start() + a<-table.row.start(a) + a<-table.element(a,'10-Fold Cross Validation',3+2*par3,TRUE) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'',1,TRUE) + a<-table.element(a,'Prediction (training)',par3+1,TRUE) + a<-table.element(a,'Prediction (testing)',par3+1,TRUE) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'Actual',1,TRUE) + for (jjj in 1:par3) a<-table.element(a,paste('C',jjj,sep=''),1,TRUE) + a<-table.element(a,'CV',1,TRUE) + for (jjj in 1:par3) a<-table.element(a,paste('C',jjj,sep=''),1,TRUE) + a<-table.element(a,'CV',1,TRUE) + a<-table.row.end(a) + for (i in 1:10) { + ind <- sample(2, nrow(x), replace=T, prob=c(0.9,0.1)) + m.ct <- ctree(as.formula(paste('as.factor(',colnames(x)[par1],') ~ .',sep='')),data =x[ind==1,]) + if (i==1) { + m.ct.i.pred <- predict(m.ct, newdata=x[ind==1,]) + m.ct.i.actu <- x[ind==1,par1] + m.ct.x.pred <- predict(m.ct, newdata=x[ind==2,]) + m.ct.x.actu <- x[ind==2,par1] + } else { + m.ct.i.pred <- c(m.ct.i.pred,predict(m.ct, newdata=x[ind==1,])) + m.ct.i.actu <- c(m.ct.i.actu,x[ind==1,par1]) + m.ct.x.pred <- c(m.ct.x.pred,predict(m.ct, newdata=x[ind==2,])) + m.ct.x.actu <- c(m.ct.x.actu,x[ind==2,par1]) + } + } + print(m.ct.i.tab <- table(m.ct.i.actu,m.ct.i.pred)) + numer <- 0 + for (i in 1:par3) { + print(m.ct.i.tab[i,i] / sum(m.ct.i.tab[i,])) + numer <- numer + m.ct.i.tab[i,i] + } + print(m.ct.i.cp <- numer / sum(m.ct.i.tab)) + print(m.ct.x.tab <- table(m.ct.x.actu,m.ct.x.pred)) + numer <- 0 + for (i in 1:par3) { + print(m.ct.x.tab[i,i] / sum(m.ct.x.tab[i,])) + numer <- numer + m.ct.x.tab[i,i] + } + print(m.ct.x.cp <- numer / sum(m.ct.x.tab)) + for (i in 1:par3) { + a<-table.row.start(a) + a<-table.element(a,paste('C',i,sep=''),1,TRUE) + for (jjj in 1:par3) a<-table.element(a,m.ct.i.tab[i,jjj]) + a<-table.element(a,round(m.ct.i.tab[i,i]/sum(m.ct.i.tab[i,]),4)) + for (jjj in 1:par3) a<-table.element(a,m.ct.x.tab[i,jjj]) + a<-table.element(a,round(m.ct.x.tab[i,i]/sum(m.ct.x.tab[i,]),4)) + a<-table.row.end(a) + } + a<-table.row.start(a) + a<-table.element(a,'Overall',1,TRUE) + for (jjj in 1:par3) a<-table.element(a,'-') + a<-table.element(a,round(m.ct.i.cp,4)) + for (jjj in 1:par3) a<-table.element(a,'-') + a<-table.element(a,round(m.ct.x.cp,4)) + a<-table.row.end(a) + a<-table.end(a) + table.save(a,file="/var/www/rcomp/tmp/1pwen1323871048.tab") + } + } m.ct.i.pred m.ct.i.actu 1 2 1 648 0 2 28 596 [1] 1 [1] 0.9551282 [1] 0.9779874 m.ct.x.pred m.ct.x.actu 1 2 1 92 0 2 2 74 [1] 1 [1] 0.9736842 [1] 0.9880952 > m Conditional inference tree with 2 terminal nodes Response: as.factor(includedhyperlinks) Inputs: Ranking, Logins, BloggedComputations, ReviewedCompendiums, includedblogs Number of observations: 144 1) includedblogs <= 40; criterion = 1, statistic = 79.625 2)* weights = 77 1) includedblogs > 40 3)* weights = 67 > postscript(file="/var/www/rcomp/tmp/2m09h1323871048.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(m) > dev.off() null device 1 > postscript(file="/var/www/rcomp/tmp/3smeb1323871048.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(x[,par1] ~ as.factor(where(m)),main='Response by Terminal Node',xlab='Terminal Node',ylab='Response') > dev.off() null device 1 > if (par2 == 'none') { + forec <- predict(m) + result <- as.data.frame(cbind(x[,par1],forec,x[,par1]-forec)) + colnames(result) <- c('Actuals','Forecasts','Residuals') + print(result) + } > if (par2 != 'none') { + print(cbind(as.factor(x[,par1]),predict(m))) + myt <- table(as.factor(x[,par1]),predict(m)) + print(myt) + } [,1] [,2] [1,] 1 1 [2,] 2 1 [3,] 1 1 [4,] 2 2 [5,] 2 2 [6,] 2 2 [7,] 1 1 [8,] 2 2 [9,] 2 2 [10,] 2 2 [11,] 2 2 [12,] 2 2 [13,] 1 1 [14,] 2 2 [15,] 1 1 [16,] 1 1 [17,] 2 2 [18,] 1 1 [19,] 2 2 [20,] 1 1 [21,] 1 1 [22,] 2 2 [23,] 1 1 [24,] 1 1 [25,] 2 2 [26,] 2 2 [27,] 2 2 [28,] 2 2 [29,] 2 2 [30,] 2 2 [31,] 1 1 [32,] 2 1 [33,] 2 2 [34,] 1 1 [35,] 2 2 [36,] 1 1 [37,] 1 1 [38,] 2 2 [39,] 1 1 [40,] 2 2 [41,] 2 2 [42,] 1 1 [43,] 2 2 [44,] 2 2 [45,] 2 2 [46,] 2 2 [47,] 2 2 [48,] 2 2 [49,] 1 1 [50,] 2 2 [51,] 1 1 [52,] 1 1 [53,] 2 2 [54,] 2 2 [55,] 2 2 [56,] 1 1 [57,] 2 2 [58,] 1 1 [59,] 1 1 [60,] 1 1 [61,] 2 2 [62,] 1 1 [63,] 1 1 [64,] 1 1 [65,] 1 1 [66,] 2 2 [67,] 2 2 [68,] 2 2 [69,] 2 2 [70,] 1 1 [71,] 2 2 [72,] 2 2 [73,] 2 2 [74,] 2 2 [75,] 1 1 [76,] 1 1 [77,] 2 2 [78,] 2 2 [79,] 1 1 [80,] 2 2 [81,] 1 1 [82,] 2 1 [83,] 1 1 [84,] 1 1 [85,] 1 1 [86,] 2 2 [87,] 2 2 [88,] 1 1 [89,] 1 1 [90,] 2 2 [91,] 2 2 [92,] 2 2 [93,] 1 1 [94,] 2 2 [95,] 1 1 [96,] 2 2 [97,] 2 2 [98,] 1 1 [99,] 1 1 [100,] 1 1 [101,] 1 1 [102,] 1 1 [103,] 1 1 [104,] 1 1 [105,] 1 1 [106,] 1 1 [107,] 2 2 [108,] 1 1 [109,] 1 1 [110,] 2 2 [111,] 1 1 [112,] 2 2 [113,] 2 2 [114,] 2 2 [115,] 1 1 [116,] 1 1 [117,] 2 2 [118,] 2 2 [119,] 2 2 [120,] 1 1 [121,] 1 1 [122,] 2 2 [123,] 1 1 [124,] 1 1 [125,] 1 1 [126,] 1 1 [127,] 2 2 [128,] 1 1 [129,] 2 2 [130,] 1 1 [131,] 1 1 [132,] 1 1 [133,] 1 1 [134,] 2 2 [135,] 1 1 [136,] 1 1 [137,] 1 1 [138,] 1 1 [139,] 1 1 [140,] 1 1 [141,] 1 1 [142,] 1 1 [143,] 2 2 [144,] 1 1 [ 0, 41) [41,157] [ 0, 41) 74 0 [41,157] 3 67 > postscript(file="/var/www/rcomp/tmp/4o0vs1323871048.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > if(par2=='none') { + op <- par(mfrow=c(2,2)) + plot(density(result$Actuals),main='Kernel Density Plot of Actuals') + plot(density(result$Residuals),main='Kernel Density Plot of Residuals') + plot(result$Forecasts,result$Actuals,main='Actuals versus Predictions',xlab='Predictions',ylab='Actuals') + plot(density(result$Forecasts),main='Kernel Density Plot of Predictions') + par(op) + } > if(par2!='none') { + plot(myt,main='Confusion Matrix',xlab='Actual',ylab='Predicted') + } > dev.off() null device 1 > if (par2 == 'none') { + detcoef <- cor(result$Forecasts,result$Actuals) + a<-table.start() + a<-table.row.start(a) + a<-table.element(a,'Goodness of Fit',2,TRUE) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'Correlation',1,TRUE) + a<-table.element(a,round(detcoef,4)) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'R-squared',1,TRUE) + a<-table.element(a,round(detcoef*detcoef,4)) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'RMSE',1,TRUE) + a<-table.element(a,round(sqrt(mean((result$Residuals)^2)),4)) + a<-table.row.end(a) + a<-table.end(a) + table.save(a,file="/var/www/rcomp/tmp/5sqrw1323871048.tab") + a<-table.start() + a<-table.row.start(a) + a<-table.element(a,'Actuals, Predictions, and Residuals',4,TRUE) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'#',header=TRUE) + a<-table.element(a,'Actuals',header=TRUE) + a<-table.element(a,'Forecasts',header=TRUE) + a<-table.element(a,'Residuals',header=TRUE) + a<-table.row.end(a) + for (i in 1:length(result$Actuals)) { + a<-table.row.start(a) + a<-table.element(a,i,header=TRUE) + a<-table.element(a,result$Actuals[i]) + a<-table.element(a,result$Forecasts[i]) + a<-table.element(a,result$Residuals[i]) + a<-table.row.end(a) + } + a<-table.end(a) + table.save(a,file="/var/www/rcomp/tmp/6pqvw1323871048.tab") + } > if (par2 != 'none') { + a<-table.start() + a<-table.row.start(a) + a<-table.element(a,'Confusion Matrix (predicted in columns / actuals in rows)',par3+1,TRUE) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'',1,TRUE) + for (i in 1:par3) { + a<-table.element(a,paste('C',i,sep=''),1,TRUE) + } + a<-table.row.end(a) + for (i in 1:par3) { + a<-table.row.start(a) + a<-table.element(a,paste('C',i,sep=''),1,TRUE) + for (j in 1:par3) { + a<-table.element(a,myt[i,j]) + } + a<-table.row.end(a) + } + a<-table.end(a) + table.save(a,file="/var/www/rcomp/tmp/7s9761323871048.tab") + } > > try(system("convert tmp/2m09h1323871048.ps tmp/2m09h1323871048.png",intern=TRUE)) character(0) > try(system("convert tmp/3smeb1323871048.ps tmp/3smeb1323871048.png",intern=TRUE)) character(0) > try(system("convert tmp/4o0vs1323871048.ps tmp/4o0vs1323871048.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 3.616 0.288 3.922