R version 2.13.0 (2011-04-13) Copyright (C) 2011 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(158258 + ,89 + ,48 + ,18 + ,20465 + ,186930 + ,57 + ,53 + ,20 + ,33629 + ,7215 + ,18 + ,0 + ,0 + ,1423 + ,129098 + ,94 + ,51 + ,27 + ,25629 + ,230587 + ,134 + ,76 + ,31 + ,54002 + ,508313 + ,260 + ,128 + ,36 + ,151036 + ,180745 + ,56 + ,62 + ,23 + ,33287 + ,185559 + ,58 + ,83 + ,30 + ,31172 + ,154581 + ,43 + ,55 + ,30 + ,28113 + ,290658 + ,95 + ,67 + ,26 + ,57803 + ,121844 + ,75 + ,50 + ,24 + ,49830 + ,184039 + ,68 + ,77 + ,30 + ,52143 + ,100324 + ,98 + ,46 + ,22 + ,21055 + ,209427 + ,114 + ,79 + ,25 + ,47007 + ,167592 + ,57 + ,55 + ,18 + ,28735 + ,154593 + ,86 + ,54 + ,22 + ,59147 + ,142018 + ,56 + ,81 + ,33 + ,78950 + ,77855 + ,59 + ,5 + ,15 + ,13497 + ,167047 + ,86 + ,74 + ,34 + ,46154 + ,27997 + ,24 + ,13 + ,18 + ,53249 + ,70824 + ,58 + ,19 + ,15 + ,10726 + ,241082 + ,99 + ,99 + ,30 + ,83700 + ,195820 + ,72 + ,38 + ,25 + ,40400 + ,141899 + ,53 + ,59 + ,34 + ,33797 + ,145433 + ,85 + ,50 + ,21 + ,36205 + ,180241 + ,30 + ,50 + ,21 + ,30165 + 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,54 + ,26 + ,42005 + ,287191 + ,64 + ,49 + ,29 + ,41152 + ,62974 + ,27 + ,26 + ,23 + ,14399 + ,130982 + ,38 + ,47 + ,25 + ,28263 + ,75555 + ,45 + ,35 + ,22 + ,17215 + ,162154 + ,54 + ,32 + ,26 + ,48140 + ,224670 + ,225 + ,55 + ,33 + ,62897 + ,115019 + ,110 + ,58 + ,24 + ,22883 + ,105038 + ,60 + ,44 + ,24 + ,41622 + ,155537 + ,52 + ,45 + ,21 + ,40715 + ,153133 + ,41 + ,49 + ,28 + ,65897 + ,165577 + ,76 + ,72 + ,27 + ,76542 + ,151517 + ,57 + ,39 + ,25 + ,37477 + ,133686 + ,58 + ,28 + ,15 + ,53216 + ,58128 + ,38 + ,24 + ,13 + ,40911 + ,245196 + ,117 + ,52 + ,36 + ,57021 + ,195576 + ,69 + ,96 + ,24 + ,73116 + ,19349 + ,12 + ,13 + ,1 + ,3895 + ,225371 + ,105 + ,38 + ,24 + ,46609 + ,152796 + ,76 + ,41 + ,31 + ,29351 + ,59117 + ,28 + ,24 + ,4 + ,2325 + ,91762 + ,23 + ,54 + ,21 + ,31747 + ,127987 + ,52 + ,59 + ,23 + ,32665 + ,113552 + ,58 + ,28 + ,23 + ,19249 + ,85338 + ,40 + ,36 + ,12 + ,15292 + ,27676 + ,22 + ,2 + ,16 + ,5842 + ,147984 + ,47 + ,83 + ,29 + ,33994 + ,122417 + ,36 + ,29 + ,26 + ,13018 + ,0 + ,0 + ,0 + ,0 + ,0 + ,91529 + ,32 + ,46 + ,25 + ,98177 + ,107205 + ,66 + ,25 + ,21 + ,37941 + ,144664 + ,44 + ,51 + ,23 + ,31032 + ,136540 + ,61 + ,59 + ,21 + ,32683 + ,76656 + ,59 + ,36 + ,21 + ,34545 + ,3616 + ,5 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,183065 + ,42 + ,40 + ,23 + ,27525 + ,144636 + ,83 + ,68 + ,33 + ,66856 + ,152826 + ,96 + ,28 + ,28 + ,28549 + ,113273 + ,38 + ,36 + ,23 + ,38610 + ,43410 + ,19 + ,7 + ,1 + ,2781 + ,175774 + ,72 + ,70 + ,29 + ,41211 + ,95401 + ,41 + ,30 + ,18 + ,22698 + ,118893 + ,54 + ,59 + ,32 + ,41194 + ,60493 + ,40 + ,3 + ,12 + ,32689 + ,19764 + ,12 + ,10 + ,2 + ,5752 + ,164062 + ,55 + ,46 + ,21 + ,26757 + ,132696 + ,32 + ,34 + ,28 + ,22527 + ,155088 + ,47 + ,54 + ,29 + ,44810 + ,11796 + ,9 + ,1 + ,2 + ,0 + ,10674 + ,9 + ,0 + ,0 + ,0 + ,142261 + ,56 + ,39 + ,18 + ,100674 + ,6836 + ,3 + ,0 + ,1 + ,0 + ,154206 + ,61 + ,48 + ,21 + ,57786 + ,5118 + ,3 + ,5 + ,0 + ,0 + ,40248 + ,16 + ,8 + ,4 + ,5444 + ,0 + ,0 + ,0 + ,0 + ,0 + ,122641 + ,46 + ,38 + ,25 + ,28470 + ,88837 + ,38 + ,21 + ,26 + ,61849 + ,7131 + ,4 + ,0 + ,0 + ,0 + ,9056 + ,14 + ,0 + ,4 + ,2179 + ,76611 + ,24 + ,15 + ,17 + ,8019 + ,132697 + ,50 + ,50 + ,21 + ,39644 + ,100681 + ,19 + ,17 + ,22 + ,23494) + ,dim=c(5 + ,144) + ,dimnames=list(c('TotTimespentinRFCsec' + ,'NumbLog' + ,'TotNumberBloggedComp' + ,'TotNumbReviewComp' + ,'CompWrittotnumbchar') + ,1:144)) > y <- array(NA,dim=c(5,144),dimnames=list(c('TotTimespentinRFCsec','NumbLog','TotNumberBloggedComp','TotNumbReviewComp','CompWrittotnumbchar'),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 = 'equal' > par1 = '3' > 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] "TotNumberBloggedComp" > x[,par1] [1] 48 53 0 51 76 128 62 83 55 67 50 77 46 79 55 54 81 5 [19] 74 13 19 99 38 59 50 50 61 81 60 52 61 60 53 76 63 0 [37] 54 44 36 83 105 37 25 64 55 41 23 67 54 68 12 86 74 56 [55] 67 40 53 26 67 36 50 48 46 53 27 38 69 93 59 5 53 40 [73] 72 51 81 27 94 71 20 34 54 49 26 47 35 32 55 58 44 45 [91] 49 72 39 28 24 52 96 13 38 41 24 54 59 28 36 2 83 29 [109] 0 46 25 51 59 36 0 0 40 68 28 36 7 70 30 59 3 10 [127] 46 34 54 1 0 39 0 48 5 8 0 38 21 0 0 15 50 17 > 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]) C1 C2 113 31 > colnames(x) [1] "TotTimespentinRFCsec" "NumbLog" "TotNumberBloggedComp" [4] "TotNumbReviewComp" "CompWrittotnumbchar" > colnames(x)[par1] [1] "TotNumberBloggedComp" > x[,par1] [1] C1 C1 C1 C1 C2 C2 C1 C2 C1 C2 C1 C2 C1 C2 C1 C1 C2 C1 C2 C1 C1 C2 C1 C1 C1 [26] C1 C1 C2 C1 C1 C1 C1 C1 C2 C1 C1 C1 C1 C1 C2 C2 C1 C1 C2 C1 C1 C1 C2 C1 C2 [51] C1 C2 C2 C1 C2 C1 C1 C1 C2 C1 C1 C1 C1 C1 C1 C1 C2 C2 C1 C1 C1 C1 C2 C1 C2 [76] C1 C2 C2 C1 C1 C1 C1 C1 C1 C1 C1 C1 C1 C1 C1 C1 C2 C1 C1 C1 C1 C2 C1 C1 C1 [101] C1 C1 C1 C1 C1 C1 C2 C1 C1 C1 C1 C1 C1 C1 C1 C1 C1 C2 C1 C1 C1 C2 C1 C1 C1 [126] C1 C1 C1 C1 C1 C1 C1 C1 C1 C1 C1 C1 C1 C1 C1 C1 C1 C1 C1 Levels: C1 C2 > if (par2 == 'none') { + m <- ctree(as.formula(paste(colnames(x)[par1],' ~ .',sep='')),data = x) + } > > #Note: the /var/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/wessaorg/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/wessaorg/rcomp/tmp/12to01324501594.tab") + } + } m.ct.i.pred m.ct.i.actu 1 2 1 920 92 2 101 177 [1] 0.9090909 [1] 0.6366906 [1] 0.8503876 m.ct.x.pred m.ct.x.actu 1 2 1 96 22 2 18 14 [1] 0.8135593 [1] 0.4375 [1] 0.7333333 > m Conditional inference tree with 3 terminal nodes Response: as.factor(TotNumberBloggedComp) Inputs: TotTimespentinRFCsec, NumbLog, TotNumbReviewComp, CompWrittotnumbchar Number of observations: 144 1) TotTimespentinRFCsec <= 137011; criterion = 1, statistic = 27.789 2)* weights = 71 1) TotTimespentinRFCsec > 137011 3) CompWrittotnumbchar <= 66616; criterion = 0.991, statistic = 9.432 4)* weights = 60 3) CompWrittotnumbchar > 66616 5)* weights = 13 > postscript(file="/var/wessaorg/rcomp/tmp/2m8du1324501594.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/wessaorg/rcomp/tmp/350wx1324501594.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,] 1 1 [3,] 1 1 [4,] 1 1 [5,] 2 1 [6,] 2 2 [7,] 1 1 [8,] 2 1 [9,] 1 1 [10,] 2 1 [11,] 1 1 [12,] 2 1 [13,] 1 1 [14,] 2 1 [15,] 1 1 [16,] 1 1 [17,] 2 2 [18,] 1 1 [19,] 2 1 [20,] 1 1 [21,] 1 1 [22,] 2 2 [23,] 1 1 [24,] 1 1 [25,] 1 1 [26,] 1 1 [27,] 1 1 [28,] 2 1 [29,] 1 2 [30,] 1 1 [31,] 1 1 [32,] 1 1 [33,] 1 1 [34,] 2 1 [35,] 1 1 [36,] 1 1 [37,] 1 1 [38,] 1 1 [39,] 1 1 [40,] 2 2 [41,] 2 1 [42,] 1 1 [43,] 1 1 [44,] 2 1 [45,] 1 1 [46,] 1 1 [47,] 1 1 [48,] 2 1 [49,] 1 1 [50,] 2 1 [51,] 1 1 [52,] 2 1 [53,] 2 2 [54,] 1 1 [55,] 2 1 [56,] 1 1 [57,] 1 1 [58,] 1 1 [59,] 2 1 [60,] 1 1 [61,] 1 1 [62,] 1 1 [63,] 1 1 [64,] 1 1 [65,] 1 1 [66,] 1 1 [67,] 2 2 [68,] 2 1 [69,] 1 1 [70,] 1 1 [71,] 1 1 [72,] 1 1 [73,] 2 1 [74,] 1 1 [75,] 2 2 [76,] 1 1 [77,] 2 1 [78,] 2 2 [79,] 1 1 [80,] 1 1 [81,] 1 1 [82,] 1 1 [83,] 1 1 [84,] 1 1 [85,] 1 1 [86,] 1 1 [87,] 1 1 [88,] 1 1 [89,] 1 1 [90,] 1 1 [91,] 1 1 [92,] 2 2 [93,] 1 1 [94,] 1 1 [95,] 1 1 [96,] 1 1 [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 1 [108,] 1 1 [109,] 1 1 [110,] 1 1 [111,] 1 1 [112,] 1 1 [113,] 1 1 [114,] 1 1 [115,] 1 1 [116,] 1 1 [117,] 1 1 [118,] 2 2 [119,] 1 1 [120,] 1 1 [121,] 1 1 [122,] 2 1 [123,] 1 1 [124,] 1 1 [125,] 1 1 [126,] 1 1 [127,] 1 1 [128,] 1 1 [129,] 1 1 [130,] 1 1 [131,] 1 1 [132,] 1 2 [133,] 1 1 [134,] 1 1 [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,] 1 1 [144,] 1 1 C1 C2 C1 111 2 C2 20 11 > postscript(file="/var/wessaorg/rcomp/tmp/4s5f31324501594.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$Residuals)^2)),4)) + a<-table.row.end(a) + a<-table.end(a) + table.save(a,file="/var/wessaorg/rcomp/tmp/5yhlf1324501594.tab") + a<-table.start() + a<-table.row.start(a) + a<-table.element(a,'Actuals, Predictions, and Residuals',4,TRUE) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'#',header=TRUE) + a<-table.element(a,'Actuals',header=TRUE) + a<-table.element(a,'Forecasts',header=TRUE) + a<-table.element(a,'Residuals',header=TRUE) + a<-table.row.end(a) + for (i in 1:length(result$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/wessaorg/rcomp/tmp/67bri1324501594.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/wessaorg/rcomp/tmp/7sptl1324501594.tab") + } > > try(system("convert tmp/2m8du1324501594.ps tmp/2m8du1324501594.png",intern=TRUE)) character(0) > try(system("convert tmp/350wx1324501594.ps tmp/350wx1324501594.png",intern=TRUE)) character(0) > try(system("convert tmp/4s5f31324501594.ps tmp/4s5f31324501594.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 3.668 0.411 4.075