R version 2.12.0 (2010-10-15) 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(1845 + ,162687 + ,95 + ,595 + ,115 + ,0 + ,48 + ,1917 + ,233285 + ,67 + ,580 + ,79 + ,1 + ,75 + ,192 + ,7215 + ,18 + ,72 + ,1 + ,0 + ,0 + ,2665 + ,164587 + ,99 + ,737 + ,158 + ,0 + ,74 + ,3709 + ,283430 + ,141 + ,1255 + ,127 + ,0 + ,92 + ,7138 + ,546996 + ,275 + ,2021 + ,278 + ,1 + ,137 + ,1888 + ,192501 + ,61 + ,606 + ,95 + ,1 + ,65 + ,1909 + ,213538 + ,64 + ,533 + ,64 + ,0 + ,97 + ,2140 + ,182282 + ,46 + ,687 + ,92 + ,0 + ,62 + ,3168 + ,336547 + ,102 + ,1074 + ,130 + ,1 + ,72 + ,1957 + ,122275 + ,77 + ,637 + ,158 + ,2 + ,50 + ,2370 + ,203938 + ,72 + ,743 + ,120 + ,0 + ,88 + ,1998 + ,119300 + ,110 + ,701 + ,87 + ,0 + ,68 + ,3203 + ,220796 + ,122 + ,1087 + ,264 + ,4 + ,79 + ,1505 + ,174005 + ,67 + ,422 + ,51 + ,4 + ,56 + ,1574 + ,156326 + ,89 + ,474 + ,85 + ,3 + ,54 + ,1965 + ,164063 + ,60 + ,483 + ,100 + ,0 + ,101 + ,1314 + ,90025 + ,63 + ,375 + ,72 + ,5 + ,13 + ,2921 + ,179987 + ,90 + ,929 + ,147 + ,0 + ,80 + ,823 + ,47066 + ,29 + ,262 + ,49 + 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+ ,0 + ,73 + ,1386 + ,147990 + ,68 + ,348 + ,72 + ,1 + ,40 + ,839 + ,87448 + ,42 + ,227 + ,27 + ,1 + ,36 + ,596 + ,27676 + ,22 + ,194 + ,59 + ,0 + ,2 + ,1684 + ,170326 + ,52 + ,413 + ,127 + ,0 + ,103 + ,1168 + ,132148 + ,38 + ,273 + ,48 + ,1 + ,30 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,1315 + ,133868 + ,36 + ,390 + ,58 + ,0 + ,78 + ,1149 + ,109001 + ,68 + ,376 + ,57 + ,0 + ,25 + ,1485 + ,158833 + ,46 + ,495 + ,60 + ,0 + ,59 + ,1529 + ,150013 + ,66 + ,448 + ,77 + ,1 + ,60 + ,962 + ,89887 + ,63 + ,313 + ,71 + ,0 + ,36 + ,78 + ,3616 + ,5 + ,14 + ,5 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,1295 + ,216479 + ,48 + ,445 + ,78 + ,0 + ,51 + ,1751 + ,177323 + ,102 + ,637 + ,76 + ,0 + ,79 + ,2142 + ,177948 + ,102 + ,593 + ,124 + ,2 + ,30 + ,1070 + ,140106 + ,41 + ,326 + ,67 + ,0 + ,43 + ,778 + ,43410 + ,19 + ,292 + ,63 + ,0 + ,7 + ,1986 + ,206059 + ,76 + ,573 + ,92 + ,1 + ,92 + ,1084 + ,109873 + ,45 + ,315 + ,58 + ,0 + ,32 + ,2400 + ,157084 + ,61 + ,683 + ,65 + ,10 + ,84 + ,731 + ,60493 + ,40 + ,174 + ,29 + ,3 + ,3 + ,285 + ,19764 + ,12 + ,75 + ,19 + ,1 + ,10 + ,1873 + ,177559 + ,57 + ,572 + ,64 + ,3 + ,47 + ,1269 + ,154169 + ,36 + ,414 + ,79 + ,0 + ,44 + ,1725 + ,164249 + ,54 + ,562 + ,104 + ,0 + ,54 + ,256 + ,11796 + ,9 + ,79 + ,22 + ,0 + ,1 + ,98 + ,10674 + ,9 + ,33 + ,7 + ,0 + ,0 + ,1435 + ,151322 + ,59 + ,487 + ,37 + ,0 + ,46 + ,41 + ,6836 + ,3 + ,11 + ,5 + ,0 + ,0 + ,1931 + ,174712 + ,68 + ,664 + ,48 + ,6 + ,51 + ,42 + ,5118 + ,3 + ,6 + ,1 + ,0 + ,5 + ,528 + ,40248 + ,16 + ,183 + ,34 + ,1 + ,8 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,1122 + ,127628 + ,51 + ,342 + ,53 + ,0 + ,38 + ,1305 + ,88837 + ,38 + ,269 + ,44 + ,0 + ,21 + ,81 + ,7131 + ,4 + ,27 + ,0 + ,1 + ,0 + ,262 + ,9056 + ,15 + ,99 + ,18 + ,0 + ,0 + ,1165 + ,97191 + ,31 + ,322 + ,52 + ,1 + ,26 + ,1405 + ,157478 + ,59 + ,367 + ,60 + ,0 + ,53 + ,1409 + ,125583 + ,23 + ,521 + ,50 + ,1 + ,31) + ,dim=c(7 + ,144) + ,dimnames=list(c('a' + ,'b' + ,'c' + ,'d' + ,'e' + ,'f' + ,'g') + ,1:144)) > y <- array(NA,dim=c(7,144),dimnames=list(c('a','b','c','d','e','f','g'),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 = '1' > #'GNU S' R Code compiled by R2WASP v. 1.0.44 () > #Author: Dr. Ian E. Holliday > #To cite this work: Ian E. Holliday, 2009, YOUR SOFTWARE TITLE (vNUMBER) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/ > #Source of accompanying publication: > #Technical description: > library(party) Loading required package: survival Loading required package: splines Loading required package: grid Loading required package: modeltools Loading required package: stats4 Loading required package: coin Loading required package: mvtnorm Loading required package: zoo Loading required package: sandwich Loading required package: strucchange Loading required package: vcd Loading required package: MASS Loading required package: colorspace > library(Hmisc) Attaching package: 'Hmisc' The following object(s) are masked from 'package:survival': untangle.specials The following object(s) are masked from 'package:base': format.pval, round.POSIXt, trunc.POSIXt, units > par1 <- as.numeric(par1) > par3 <- as.numeric(par3) > x <- data.frame(t(y)) > is.data.frame(x) [1] TRUE > x <- x[!is.na(x[,par1]),] > k <- length(x[1,]) > n <- length(x[,1]) > colnames(x)[par1] [1] "a" > x[,par1] [1] 1845 1917 192 2665 3709 7138 1888 1909 2140 3168 1957 2370 1998 3203 1505 [16] 1574 1965 1314 2921 823 1289 2818 1792 2474 1994 1806 2177 1458 3057 2487 [31] 1914 1825 2509 3634 2608 1 2157 1978 2224 2215 2538 1881 1113 2380 1365 [46] 1294 756 2465 2327 2787 658 2013 2666 2086 2067 1776 2045 1047 1190 2932 [61] 1868 2316 1392 1355 1326 1587 2336 2898 1118 340 3224 1552 1551 1794 2728 [76] 1580 2414 2640 1203 1313 1207 2246 1076 1638 1208 1868 2829 1209 1463 1610 [91] 1865 2444 1253 1468 979 2365 1890 223 2527 2186 778 1194 1424 1386 839 [106] 596 1684 1168 0 1315 1149 1485 1529 962 78 0 1295 1751 2142 1070 [121] 778 1986 1084 2400 731 285 1873 1269 1725 256 98 1435 41 1931 42 [136] 528 0 1122 1305 81 262 1165 1405 1409 > if (par2 == 'kmeans') { + cl <- kmeans(x[,par1], par3) + print(cl) + clm <- matrix(cbind(cl$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]) [ 0,1638) [1638,7138] 72 72 > colnames(x) [1] "a" "b" "c" "d" "e" "f" "g" > colnames(x)[par1] [1] "a" > x[,par1] [1] [1638,7138] [1638,7138] [ 0,1638) [1638,7138] [1638,7138] [1638,7138] [7] [1638,7138] [1638,7138] [1638,7138] [1638,7138] [1638,7138] [1638,7138] [13] [1638,7138] [1638,7138] [ 0,1638) [ 0,1638) [1638,7138] [ 0,1638) [19] [1638,7138] [ 0,1638) [ 0,1638) [1638,7138] [1638,7138] [1638,7138] [25] [1638,7138] [1638,7138] [1638,7138] [ 0,1638) [1638,7138] [1638,7138] [31] [1638,7138] [1638,7138] [1638,7138] [1638,7138] [1638,7138] [ 0,1638) [37] [1638,7138] [1638,7138] [1638,7138] [1638,7138] [1638,7138] [1638,7138] [43] [ 0,1638) [1638,7138] [ 0,1638) [ 0,1638) [ 0,1638) [1638,7138] [49] [1638,7138] [1638,7138] [ 0,1638) [1638,7138] [1638,7138] [1638,7138] [55] [1638,7138] [1638,7138] [1638,7138] [ 0,1638) [ 0,1638) [1638,7138] [61] [1638,7138] [1638,7138] [ 0,1638) [ 0,1638) [ 0,1638) [ 0,1638) [67] [1638,7138] [1638,7138] [ 0,1638) [ 0,1638) [1638,7138] [ 0,1638) [73] [ 0,1638) [1638,7138] [1638,7138] [ 0,1638) [1638,7138] [1638,7138] [79] [ 0,1638) [ 0,1638) [ 0,1638) [1638,7138] [ 0,1638) [1638,7138] [85] [ 0,1638) [1638,7138] [1638,7138] [ 0,1638) [ 0,1638) [ 0,1638) [91] [1638,7138] [1638,7138] [ 0,1638) [ 0,1638) [ 0,1638) [1638,7138] [97] [1638,7138] [ 0,1638) [1638,7138] [1638,7138] [ 0,1638) [ 0,1638) [103] [ 0,1638) [ 0,1638) [ 0,1638) [ 0,1638) [1638,7138] [ 0,1638) [109] [ 0,1638) [ 0,1638) [ 0,1638) [ 0,1638) [ 0,1638) [ 0,1638) [115] [ 0,1638) [ 0,1638) [ 0,1638) [1638,7138] [1638,7138] [ 0,1638) [121] [ 0,1638) [1638,7138] [ 0,1638) [1638,7138] [ 0,1638) [ 0,1638) [127] [1638,7138] [ 0,1638) [1638,7138] [ 0,1638) [ 0,1638) [ 0,1638) [133] [ 0,1638) [1638,7138] [ 0,1638) [ 0,1638) [ 0,1638) [ 0,1638) [139] [ 0,1638) [ 0,1638) [ 0,1638) [ 0,1638) [ 0,1638) [ 0,1638) Levels: [ 0,1638) [1638,7138] > 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/1503y1324662504.tab") + } + } m.ct.i.pred m.ct.i.actu 1 2 1 608 46 2 17 634 [1] 0.9296636 [1] 0.9738863 [1] 0.9517241 m.ct.x.pred m.ct.x.actu 1 2 1 62 4 2 5 64 [1] 0.939394 [1] 0.9275362 [1] 0.9333333 > m Conditional inference tree with 3 terminal nodes Response: as.factor(a) Inputs: b, c, d, e, f, g Number of observations: 144 1) d <= 500; criterion = 1, statistic = 79.231 2) g <= 67; criterion = 0.998, statistic = 13.04 3)* weights = 62 2) g > 67 4)* weights = 7 1) d > 500 5)* weights = 75 > postscript(file="/var/www/rcomp/tmp/2cx9h1324662504.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/33lfp1324662504.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,] 2 2 [2,] 2 2 [3,] 1 1 [4,] 2 2 [5,] 2 2 [6,] 2 2 [7,] 2 2 [8,] 2 2 [9,] 2 2 [10,] 2 2 [11,] 2 2 [12,] 2 2 [13,] 2 2 [14,] 2 2 [15,] 1 1 [16,] 1 1 [17,] 2 1 [18,] 1 1 [19,] 2 2 [20,] 1 1 [21,] 1 1 [22,] 2 2 [23,] 2 2 [24,] 2 2 [25,] 2 2 [26,] 2 2 [27,] 2 2 [28,] 1 1 [29,] 2 2 [30,] 2 2 [31,] 2 2 [32,] 2 2 [33,] 2 2 [34,] 2 2 [35,] 2 2 [36,] 1 1 [37,] 2 2 [38,] 2 2 [39,] 2 2 [40,] 2 2 [41,] 2 2 [42,] 2 2 [43,] 1 1 [44,] 2 2 [45,] 1 1 [46,] 1 1 [47,] 1 1 [48,] 2 2 [49,] 2 2 [50,] 2 2 [51,] 1 1 [52,] 2 2 [53,] 2 2 [54,] 2 2 [55,] 2 2 [56,] 2 2 [57,] 2 2 [58,] 1 1 [59,] 1 1 [60,] 2 2 [61,] 2 2 [62,] 2 2 [63,] 1 1 [64,] 1 1 [65,] 1 1 [66,] 1 1 [67,] 2 2 [68,] 2 2 [69,] 1 1 [70,] 1 1 [71,] 2 2 [72,] 1 2 [73,] 1 2 [74,] 2 2 [75,] 2 2 [76,] 1 1 [77,] 2 2 [78,] 2 2 [79,] 1 1 [80,] 1 1 [81,] 1 1 [82,] 2 2 [83,] 1 1 [84,] 2 2 [85,] 1 1 [86,] 2 2 [87,] 2 2 [88,] 1 1 [89,] 1 1 [90,] 1 2 [91,] 2 2 [92,] 2 2 [93,] 1 1 [94,] 1 2 [95,] 1 1 [96,] 2 2 [97,] 2 2 [98,] 1 1 [99,] 2 2 [100,] 2 2 [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,] 2 2 [120,] 1 1 [121,] 1 1 [122,] 2 2 [123,] 1 1 [124,] 2 2 [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,] 1 1 [144,] 1 2 [ 0,1638) [1638,7138] [ 0,1638) 67 5 [1638,7138] 2 70 > postscript(file="/var/www/rcomp/tmp/47bar1324662505.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/54beu1324662505.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/6jvo71324662505.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/78x701324662505.tab") + } > > try(system("convert tmp/2cx9h1324662504.ps tmp/2cx9h1324662504.png",intern=TRUE)) character(0) > try(system("convert tmp/33lfp1324662504.ps tmp/33lfp1324662504.png",intern=TRUE)) character(0) > try(system("convert tmp/47bar1324662505.ps tmp/47bar1324662505.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 2.750 0.140 2.879