R version 3.0.2 (2013-09-25) -- "Frisbee Sailing" Copyright (C) 2013 The R Foundation for Statistical Computing Platform: i686-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(13 + ,13 + ,14 + ,13 + ,3 + ,12 + ,12 + ,8 + ,13 + ,5 + ,15 + ,10 + ,12 + ,16 + ,6 + ,12 + ,9 + ,7 + ,12 + ,6 + ,10 + ,10 + ,10 + ,11 + ,5 + ,12 + ,12 + ,7 + ,12 + ,3 + ,15 + ,13 + ,16 + ,18 + ,8 + ,9 + ,12 + ,11 + ,11 + ,4 + ,12 + ,12 + ,14 + ,14 + ,4 + ,11 + ,6 + ,6 + ,9 + ,4 + ,11 + ,5 + ,16 + ,14 + ,6 + ,11 + ,12 + ,11 + ,12 + ,6 + ,15 + ,11 + ,16 + ,11 + ,5 + ,7 + ,14 + ,12 + ,12 + ,4 + ,11 + ,14 + ,7 + ,13 + ,6 + ,11 + ,12 + ,13 + ,11 + ,4 + ,10 + ,12 + ,11 + ,12 + ,6 + ,14 + ,11 + ,15 + ,16 + ,6 + ,10 + ,11 + ,7 + ,9 + ,4 + ,6 + ,7 + ,9 + ,11 + ,4 + ,11 + ,9 + ,7 + ,13 + ,2 + ,15 + ,11 + ,14 + ,15 + ,7 + ,11 + ,11 + ,15 + ,10 + ,5 + ,12 + ,12 + ,7 + ,11 + ,4 + ,14 + ,12 + ,15 + ,13 + ,6 + ,15 + ,11 + ,17 + ,16 + ,6 + ,9 + ,11 + ,15 + ,15 + ,7 + ,13 + ,8 + ,14 + ,14 + ,5 + ,13 + ,9 + ,14 + ,14 + ,6 + ,16 + ,12 + ,8 + ,14 + ,4 + ,13 + ,10 + ,8 + ,8 + ,4 + ,12 + ,10 + ,14 + ,13 + ,7 + ,14 + ,12 + ,14 + ,15 + ,7 + ,11 + ,8 + ,8 + ,13 + ,4 + ,9 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,12 + ,11 + ,16 + ,13 + ,4 + ,13 + ,12 + ,14 + ,14 + ,6 + ,15 + ,12 + ,14 + ,16 + ,4 + ,8 + ,10 + ,10 + ,6 + ,4 + ,12 + ,12 + ,10 + ,13 + ,4 + ,10 + ,13 + ,4 + ,13 + ,6 + ,8 + ,12 + ,8 + ,14 + ,5 + ,10 + ,15 + ,15 + ,15 + ,6 + ,15 + ,11 + ,16 + ,14 + ,6 + ,16 + ,12 + ,12 + ,15 + ,8 + ,13 + ,11 + ,12 + ,13 + ,7 + ,16 + ,12 + ,15 + ,16 + ,7 + ,9 + ,11 + ,9 + ,12 + ,4 + ,14 + ,10 + ,12 + ,15 + ,6 + ,14 + ,11 + ,14 + ,12 + ,6 + ,12 + ,11 + ,11 + ,14 + ,2) + ,dim=c(5 + ,156) + ,dimnames=list(c('Popularity' + ,'Findingfriends' + ,'Knowingpeople' + ,'Liked' + ,'Celebrity') + ,1:156)) > y <- array(NA,dim=c(5,156),dimnames=list(c('Popularity','Findingfriends','Knowingpeople','Liked','Celebrity'),1:156)) > for (i in 1:dim(x)[1]) + { + for (j in 1:dim(x)[2]) + { + y[i,j] <- as.numeric(x[i,j]) + } + } > par20 = '' > par19 = '' > par18 = '' > par17 = '' > par16 = '' > par15 = '' > par14 = '' > par13 = '' > par12 = '' > par11 = '' > par10 = '' > par9 = '' > par8 = '' > par7 = '' > par6 = '' > par5 = '' > par4 = 'no' > par3 = '' > par2 = 'none' > 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 Attaching package: 'zoo' The following objects are masked from 'package:base': as.Date, as.Date.numeric Loading required package: sandwich Loading required package: strucchange Loading required package: vcd Loading required package: MASS Loading required package: colorspace > library(Hmisc) Hmisc library by Frank E Harrell Jr Type library(help='Hmisc'), ?Overview, or ?Hmisc.Overview') to see overall documentation. NOTE:Hmisc no longer redefines [.factor to drop unused levels when subsetting. To get the old behavior of Hmisc type dropUnusedLevels(). Attaching package: 'Hmisc' The following object is masked from 'package:survival': untangle.specials The following objects 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] "Knowingpeople" > x[,par1] [1] 14 8 12 7 10 7 16 11 14 6 16 11 16 12 7 13 11 15 7 9 7 14 15 7 15 [26] 17 15 14 14 8 8 14 14 8 11 16 10 8 14 16 13 5 8 10 8 13 15 6 12 16 [51] 5 15 12 8 13 14 12 16 10 15 8 16 19 14 6 13 15 7 13 4 14 13 11 14 12 [76] 15 14 13 8 6 7 13 13 11 5 12 8 11 14 9 10 13 16 16 11 8 4 7 14 11 [101] 17 15 17 5 4 10 11 15 10 9 12 15 7 13 12 14 14 8 15 12 12 16 9 15 15 [126] 6 14 15 10 6 14 12 8 11 13 9 15 13 15 14 16 14 14 10 10 4 8 15 16 12 [151] 12 15 9 12 14 11 > 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]) 4 5 6 7 8 9 10 11 12 13 14 15 16 17 19 4 4 6 10 15 6 10 12 15 14 23 20 13 3 1 > colnames(x) [1] "Popularity" "Findingfriends" "Knowingpeople" "Liked" [5] "Celebrity" > colnames(x)[par1] [1] "Knowingpeople" > x[,par1] [1] 14 8 12 7 10 7 16 11 14 6 16 11 16 12 7 13 11 15 7 9 7 14 15 7 15 [26] 17 15 14 14 8 8 14 14 8 11 16 10 8 14 16 13 5 8 10 8 13 15 6 12 16 [51] 5 15 12 8 13 14 12 16 10 15 8 16 19 14 6 13 15 7 13 4 14 13 11 14 12 [76] 15 14 13 8 6 7 13 13 11 5 12 8 11 14 9 10 13 16 16 11 8 4 7 14 11 [101] 17 15 17 5 4 10 11 15 10 9 12 15 7 13 12 14 14 8 15 12 12 16 9 15 15 [126] 6 14 15 10 6 14 12 8 11 13 9 15 13 15 14 16 14 14 10 10 4 8 15 16 12 [151] 12 15 9 12 14 11 > if (par2 == 'none') { + m <- ctree(as.formula(paste(colnames(x)[par1],' ~ .',sep='')),data = x) + } > > #Note: the /var/fisher/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/fisher/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/fisher/rcomp/tmp/14wra1386626385.tab") + } + } > m Conditional inference tree with 5 terminal nodes Response: Knowingpeople Inputs: Popularity, Findingfriends, Liked, Celebrity Number of observations: 156 1) Popularity <= 11; criterion = 1, statistic = 52.817 2) Celebrity <= 4; criterion = 0.986, statistic = 8.527 3)* weights = 34 2) Celebrity > 4 4)* weights = 27 1) Popularity > 11 5) Celebrity <= 4; criterion = 1, statistic = 20.758 6)* weights = 16 5) Celebrity > 4 7) Popularity <= 13; criterion = 0.999, statistic = 14.706 8)* weights = 28 7) Popularity > 13 9)* weights = 51 > postscript(file="/var/fisher/rcomp/tmp/25l3b1386626385.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/fisher/rcomp/tmp/3zv1x1386626385.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) + } Actuals Forecasts Residuals 1 14 10.00000 4.0000000 2 8 12.28571 -4.2857143 3 12 14.35294 -2.3529412 4 7 12.28571 -5.2857143 5 10 10.55556 -0.5555556 6 7 10.00000 -3.0000000 7 16 14.35294 1.6470588 8 11 8.50000 2.5000000 9 14 10.00000 4.0000000 10 6 8.50000 -2.5000000 11 16 10.55556 5.4444444 12 11 10.55556 0.4444444 13 16 14.35294 1.6470588 14 12 8.50000 3.5000000 15 7 10.55556 -3.5555556 16 13 8.50000 4.5000000 17 11 10.55556 0.4444444 18 15 14.35294 0.6470588 19 7 8.50000 -1.5000000 20 9 8.50000 0.5000000 21 7 8.50000 -1.5000000 22 14 14.35294 -0.3529412 23 15 10.55556 4.4444444 24 7 10.00000 -3.0000000 25 15 14.35294 0.6470588 26 17 14.35294 2.6470588 27 15 10.55556 4.4444444 28 14 12.28571 1.7142857 29 14 12.28571 1.7142857 30 8 10.00000 -2.0000000 31 8 10.00000 -2.0000000 32 14 12.28571 1.7142857 33 14 14.35294 -0.3529412 34 8 8.50000 -0.5000000 35 11 8.50000 2.5000000 36 16 14.35294 1.6470588 37 10 12.28571 -2.2857143 38 8 10.55556 -2.5555556 39 14 12.28571 1.7142857 40 16 14.35294 1.6470588 41 13 14.35294 -1.3529412 42 5 10.00000 -5.0000000 43 8 8.50000 -0.5000000 44 10 8.50000 1.5000000 45 8 10.55556 -2.5555556 46 13 14.35294 -1.3529412 47 15 14.35294 0.6470588 48 6 8.50000 -2.5000000 49 12 10.55556 1.4444444 50 16 12.28571 3.7142857 51 5 10.55556 -5.5555556 52 15 10.55556 4.4444444 53 12 12.28571 -0.2857143 54 8 8.50000 -0.5000000 55 13 14.35294 -1.3529412 56 14 12.28571 1.7142857 57 12 8.50000 3.5000000 58 16 14.35294 1.6470588 59 10 8.50000 1.5000000 60 15 14.35294 0.6470588 61 8 8.50000 -0.5000000 62 16 14.35294 1.6470588 63 19 14.35294 4.6470588 64 14 14.35294 -0.3529412 65 6 10.55556 -4.5555556 66 13 14.35294 -1.3529412 67 15 10.55556 4.4444444 68 7 12.28571 -5.2857143 69 13 14.35294 -1.3529412 70 4 8.50000 -4.5000000 71 14 14.35294 -0.3529412 72 13 12.28571 0.7142857 73 11 10.55556 0.4444444 74 14 10.55556 3.4444444 75 12 12.28571 -0.2857143 76 15 12.28571 2.7142857 77 14 12.28571 1.7142857 78 13 12.28571 0.7142857 79 8 10.00000 -2.0000000 80 6 8.50000 -2.5000000 81 7 8.50000 -1.5000000 82 13 14.35294 -1.3529412 83 13 14.35294 -1.3529412 84 11 10.55556 0.4444444 85 5 10.00000 -5.0000000 86 12 12.28571 -0.2857143 87 8 8.50000 -0.5000000 88 11 12.28571 -1.2857143 89 14 14.35294 -0.3529412 90 9 8.50000 0.5000000 91 10 14.35294 -4.3529412 92 13 10.55556 2.4444444 93 16 14.35294 1.6470588 94 16 14.35294 1.6470588 95 11 12.28571 -1.2857143 96 8 8.50000 -0.5000000 97 4 10.55556 -6.5555556 98 7 8.50000 -1.5000000 99 14 10.55556 3.4444444 100 11 12.28571 -1.2857143 101 17 14.35294 2.6470588 102 15 14.35294 0.6470588 103 17 14.35294 2.6470588 104 5 8.50000 -3.5000000 105 4 8.50000 -4.5000000 106 10 14.35294 -4.3529412 107 11 8.50000 2.5000000 108 15 14.35294 0.6470588 109 10 8.50000 1.5000000 110 9 8.50000 0.5000000 111 12 10.55556 1.4444444 112 15 12.28571 2.7142857 113 7 10.55556 -3.5555556 114 13 14.35294 -1.3529412 115 12 14.35294 -2.3529412 116 14 14.35294 -0.3529412 117 14 14.35294 -0.3529412 118 8 10.55556 -2.5555556 119 15 14.35294 0.6470588 120 12 10.00000 2.0000000 121 12 10.00000 2.0000000 122 16 14.35294 1.6470588 123 9 8.50000 0.5000000 124 15 12.28571 2.7142857 125 15 14.35294 0.6470588 126 6 12.28571 -6.2857143 127 14 14.35294 -0.3529412 128 15 12.28571 2.7142857 129 10 10.55556 -0.5555556 130 6 8.50000 -2.5000000 131 14 14.35294 -0.3529412 132 12 14.35294 -2.3529412 133 8 8.50000 -0.5000000 134 11 12.28571 -1.2857143 135 13 14.35294 -1.3529412 136 9 10.00000 -1.0000000 137 15 14.35294 0.6470588 138 13 8.50000 4.5000000 139 15 14.35294 0.6470588 140 14 12.28571 1.7142857 141 16 10.00000 6.0000000 142 14 12.28571 1.7142857 143 14 10.00000 4.0000000 144 10 8.50000 1.5000000 145 10 10.00000 0.0000000 146 4 10.55556 -6.5555556 147 8 10.55556 -2.5555556 148 15 10.55556 4.4444444 149 16 14.35294 1.6470588 150 12 14.35294 -2.3529412 151 12 12.28571 -0.2857143 152 15 14.35294 0.6470588 153 9 8.50000 0.5000000 154 12 14.35294 -2.3529412 155 14 14.35294 -0.3529412 156 11 10.00000 1.0000000 > if (par2 != 'none') { + print(cbind(as.factor(x[,par1]),predict(m))) + myt <- table(as.factor(x[,par1]),predict(m)) + print(myt) + } > postscript(file="/var/fisher/rcomp/tmp/4a67e1386626385.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$Residuals)^2)),4)) + a<-table.row.end(a) + a<-table.end(a) + table.save(a,file="/var/fisher/rcomp/tmp/5c1y51386626385.tab") + a<-table.start() + a<-table.row.start(a) + a<-table.element(a,'Actuals, Predictions, and Residuals',4,TRUE) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'#',header=TRUE) + a<-table.element(a,'Actuals',header=TRUE) + a<-table.element(a,'Forecasts',header=TRUE) + a<-table.element(a,'Residuals',header=TRUE) + a<-table.row.end(a) + for (i in 1:length(result$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/fisher/rcomp/tmp/6ybew1386626386.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/fisher/rcomp/tmp/74grm1386626386.tab") + } > > try(system("convert tmp/25l3b1386626385.ps tmp/25l3b1386626385.png",intern=TRUE)) character(0) > try(system("convert tmp/3zv1x1386626385.ps tmp/3zv1x1386626385.png",intern=TRUE)) character(0) > try(system("convert tmp/4a67e1386626385.ps tmp/4a67e1386626385.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 8.122 1.192 9.316