w7 - RP (no catergorization)

*The author of this computation has been verified*

R Software Module: /rwasp_regression_trees1.wasp (opens new window with default values)

Title produced by software: Recursive Partitioning (Regression Trees)

Date of computation: Sun, 26 Dec 2010 14:36:56 +0000

Cite this page as follows:

Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL http://www.freestatistics.org/blog/date/2010/Dec/26/t1293374281z7n3hlyn3i4m539.htm/, Retrieved Sun, 26 Dec 2010 15:38:04 +0100

BibTeX entries for LaTeX users:

@Manual{KEY, author = {{YOUR NAME}}, publisher = {Office for Research Development and Education}, title = {Statistical Computations at FreeStatistics.org, URL http://www.freestatistics.org/blog/date/2010/Dec/26/t1293374281z7n3hlyn3i4m539.htm/}, year = {2010}, } @Manual{R, title = {R: A Language and Environment for Statistical Computing}, author = {{R Development Core Team}}, organization = {R Foundation for Statistical Computing}, address = {Vienna, Austria}, year = {2010}, note = {{ISBN} 3-900051-07-0}, url = {http://www.R-project.org}, }

Original text written by user:

IsPrivate?

No (this computation is public)

User-defined keywords:

Dataseries X:

» Textbox « » Textfile « » CSV «

13 13 14 13 12 12 8 13 15 10 12 16 12 9 7 12 10 10 10 11 12 12 7 12 15 13 16 18 9 12 11 11 12 12 14 14 11 6 6 9 11 5 16 14 11 12 11 12 15 11 16 11 7 14 12 12 11 14 7 13 11 12 13 11 10 12 11 12 14 11 15 16 10 11 7 9 6 7 9 11 11 9 7 13 15 11 14 15 11 11 15 10 12 12 7 11 14 12 15 13 15 11 17 16 9 11 15 15 13 8 14 14 13 9 14 14 16 12 8 14 13 10 8 8 12 10 14 13 14 12 14 15 11 8 8 13 9 12 11 11 16 11 16 15 12 12 10 15 10 7 8 9 13 11 14 13 16 11 16 16 14 12 13 13 15 9 5 11 5 15 8 12 8 11 10 12 11 11 8 12 16 11 13 14 17 11 15 14 9 15 6 8 9 11 12 13 13 12 16 16 10 12 5 13 6 9 15 11 12 12 12 14 8 12 8 13 14 13 13 13 12 11 14 13 11 9 12 12 16 9 16 16 8 11 10 15 15 11 15 15 7 12 8 12 16 12 16 14 14 9 19 12 16 11 14 15 9 9 6 12 14 12 13 13 11 12 15 12 13 12 7 12 15 12 13 13 5 14 4 5 15 11 14 13 13 12 13 13 11 11 11 14 11 6 14 17 12 10 12 13 12 12 15 13 12 13 14 12 12 8 13 13 14 12 8 14 6 12 6 11 7 12 7 12 14 6 13 12 14 11 13 16 10 10 11 12 etc...

Output produced by software:

Enter (or paste) a matrix (table) containing all data (time) series. Every column represents a different variable and must be delimited by a space or Tab. Every row represents a period in time (or category) and must be delimited by hard returns. The easiest way to enter data is to copy and paste a block of spreadsheet cells. Please, do not use commas or spaces to seperate groups of digits! Summary of computational transaction Raw Input view raw input (R code) Raw Output view raw output of R engine Computing time 7 seconds R Server 'Gwilym Jenkins' @ 72.249.127.135 R Framework error message The field 'Names of X columns' contains a hard return which cannot be interpreted. Please, resubmit your request without hard returns in the 'Names of X columns'. Goodness of Fit Correlation 0.6506 R-squared 0.4233 RMSE 2.223 Actuals, Predictions, and Residuals # Actuals Forecasts Residuals 1 13 12.3783783783784 0.621621621621621 2 12 11.0645161290323 0.935483870967742 3 15 14.2884615384615 0.711538461538462 4 12 9.30555555555556 2.69444444444444 5 10 9.30555555555556 0.694444444444445 6 12 9.30555555555556 2.69444444444444 7 15 14.2884615384615 0.711538461538462 8 9 9.30555555555556 -0.305555555555555 9 12 14.2884615384615 -2.28846153846154 10 11 9.30555555555556 1.69444444444444 11 11 14.2884615384615 -3.28846153846154 12 11 9.30555555555556 1.69444444444444 13 15 12.3783783783784 2.62162162162162 14 7 12.3783783783784 -5.37837837837838 15 11 11.0645161290323 -0.064516129032258 16 11 12.3783783783784 -1.37837837837838 17 10 9.30555555555556 0.694444444444445 18 14 14.2884615384615 -0.288461538461538 19 10 9.30555555555556 0.694444444444445 20 6 9.30555555555556 -3.30555555555556 21 11 11.0645161290323 -0.064516129032258 22 15 14.2884615384615 0.711538461538462 23 11 12.3783783783784 -1.37837837837838 24 12 9.30555555555556 2.69444444444444 25 14 12.3783783783784 1.62162162162162 26 15 14.2884615384615 0.711538461538462 27 9 14.2884615384615 -5.28846153846154 28 13 14.2884615384615 -1.28846153846154 29 13 14.2884615384615 -1.28846153846154 30 16 11.0645161290323 4.93548387096774 31 13 9.30555555555556 3.69444444444444 32 12 12.3783783783784 -0.378378378378379 33 14 14.2884615384615 -0.288461538461538 34 11 11.0645161290323 -0.064516129032258 35 9 9.30555555555556 -0.305555555555555 36 16 14.2884615384615 1.71153846153846 37 12 11.0645161290323 0.935483870967742 38 10 9.30555555555556 0.694444444444445 39 13 12.3783783783784 0.621621621621621 40 16 14.2884615384615 1.71153846153846 41 14 12.3783783783784 1.62162162162162 42 15 9.30555555555556 5.69444444444444 43 5 9.30555555555556 -4.30555555555556 44 8 9.30555555555556 -1.30555555555556 45 11 9.30555555555556 1.69444444444444 46 16 14.2884615384615 1.71153846153846 47 17 14.2884615384615 2.71153846153846 48 9 9.30555555555556 -0.305555555555555 49 9 12.3783783783784 -3.37837837837838 50 13 14.2884615384615 -1.28846153846154 51 10 11.0645161290323 -1.06451612903226 52 6 12.3783783783784 -6.37837837837838 53 12 14.2884615384615 -2.28846153846154 54 8 11.0645161290323 -3.06451612903226 55 14 12.3783783783784 1.62162162162162 56 12 12.3783783783784 -0.378378378378379 57 11 12.3783783783784 -1.37837837837838 58 16 14.2884615384615 1.71153846153846 59 8 11.0645161290323 -3.06451612903226 60 15 14.2884615384615 0.711538461538462 61 7 9.30555555555556 -2.30555555555556 62 16 14.2884615384615 1.71153846153846 63 14 12.3783783783784 1.62162162162162 64 16 14.2884615384615 1.71153846153846 65 9 9.30555555555556 -0.305555555555555 66 14 12.3783783783784 1.62162162162162 67 11 12.3783783783784 -1.37837837837838 68 13 9.30555555555556 3.69444444444444 69 15 12.3783783783784 2.62162162162162 70 5 9.30555555555556 -4.30555555555556 71 15 12.3783783783784 2.62162162162162 72 13 12.3783783783784 0.621621621621621 73 11 11.0645161290323 -0.064516129032258 74 11 14.2884615384615 -3.28846153846154 75 12 12.3783783783784 -0.378378378378379 76 12 12.3783783783784 -0.378378378378379 77 12 12.3783783783784 -0.378378378378379 78 12 12.3783783783784 -0.378378378378379 79 14 11.0645161290323 2.93548387096774 80 6 9.30555555555556 -3.30555555555556 81 7 9.30555555555556 -2.30555555555556 82 14 12.3783783783784 1.62162162162162 83 14 14.2884615384615 -0.288461538461538 84 10 9.30555555555556 0.694444444444445 85 13 9.30555555555556 3.69444444444444 86 12 12.3783783783784 -0.378378378378379 87 9 9.30555555555556 -0.305555555555555 88 12 11.0645161290323 0.935483870967742 89 16 14.2884615384615 1.71153846153846 90 10 9.30555555555556 0.694444444444445 91 14 11.0645161290323 2.93548387096774 92 10 14.2884615384615 -4.28846153846154 93 16 14.2884615384615 1.71153846153846 94 15 12.3783783783784 2.62162162162162 95 12 9.30555555555556 2.69444444444444 96 10 9.30555555555556 0.694444444444445 97 8 11.0645161290323 -3.06451612903226 98 8 9.30555555555556 -1.30555555555556 99 11 14.2884615384615 -3.28846153846154 100 13 11.0645161290323 1.93548387096774 101 16 14.2884615384615 1.71153846153846 102 16 14.2884615384615 1.71153846153846 103 14 14.2884615384615 -0.288461538461538 104 11 11.0645161290323 -0.064516129032258 105 4 9.30555555555556 -5.30555555555556 106 14 11.0645161290323 2.93548387096774 107 9 11.0645161290323 -2.06451612903226 108 14 14.2884615384615 -0.288461538461538 109 8 11.0645161290323 -3.06451612903226 110 8 11.0645161290323 -3.06451612903226 111 11 14.2884615384615 -3.28846153846154 112 12 12.3783783783784 -0.378378378378379 113 11 11.0645161290323 -0.064516129032258 114 14 14.2884615384615 -0.288461538461538 115 15 14.2884615384615 0.711538461538462 116 16 14.2884615384615 1.71153846153846 117 16 14.2884615384615 1.71153846153846 118 11 11.0645161290323 -0.064516129032258 119 14 14.2884615384615 -0.288461538461538 120 14 12.3783783783784 1.62162162162162 121 12 12.3783783783784 -0.378378378378379 122 14 12.3783783783784 1.62162162162162 123 8 9.30555555555556 -1.30555555555556 124 13 14.2884615384615 -1.28846153846154 125 16 14.2884615384615 1.71153846153846 126 12 11.0645161290323 0.935483870967742 127 16 14.2884615384615 1.71153846153846 128 12 12.3783783783784 -0.378378378378379 129 11 11.0645161290323 -0.064516129032258 130 4 9.30555555555556 -5.30555555555556 131 16 14.2884615384615 1.71153846153846 132 15 12.3783783783784 2.62162162162162 133 10 11.0645161290323 -1.06451612903226 134 13 11.0645161290323 1.93548387096774 135 15 14.2884615384615 0.711538461538462 136 12 11.0645161290323 0.935483870967742 137 14 14.2884615384615 -0.288461538461538 138 7 12.3783783783784 -5.37837837837838 139 19 14.2884615384615 4.71153846153846 140 12 14.2884615384615 -2.28846153846154 141 12 12.3783783783784 -0.378378378378379 142 13 14.2884615384615 -1.28846153846154 143 15 14.2884615384615 0.711538461538462 144 8 9.30555555555556 -1.30555555555556 145 12 11.0645161290323 0.935483870967742 146 10 11.0645161290323 -1.06451612903226 147 8 11.0645161290323 -3.06451612903226 148 10 14.2884615384615 -4.28846153846154 149 15 14.2884615384615 0.711538461538462 150 16 14.2884615384615 1.71153846153846 151 13 12.3783783783784 0.621621621621621 152 16 14.2884615384615 1.71153846153846 153 9 9.30555555555556 -0.305555555555555 154 14 14.2884615384615 -0.288461538461538 155 14 12.3783783783784 1.62162162162162 156 12 11.0645161290323 0.935483870967742

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/Dec/26/t1293374281z7n3hlyn3i4m539/2wuzc1293374209.png (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/26/t1293374281z7n3hlyn3i4m539/2wuzc1293374209.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/26/t1293374281z7n3hlyn3i4m539/3wuzc1293374209.png (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/26/t1293374281z7n3hlyn3i4m539/3wuzc1293374209.ps (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/26/t1293374281z7n3hlyn3i4m539/4olyf1293374209.png (open in new window) http://www.freestatistics.org/blog/date/2010/Dec/26/t1293374281z7n3hlyn3i4m539/4olyf1293374209.ps (open in new window)

Parameters (Session):

par1 = 1 ; par2 = none ; par3 = 3 ; par4 = no ;

Parameters (R input):

par1 = 1 ; par2 = none ; par3 = 3 ; par4 = no ;

R code (references can be found in the software module):

library(party) library(Hmisc) par1 <- as.numeric(par1) par3 <- as.numeric(par3) x <- data.frame(t(y)) is.data.frame(x) x <- x[!is.na(x[,par1]),] k <- length(x[1,]) n <- length(x[,1]) colnames(x)[par1] x[,par1] 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]) colnames(x) colnames(x)[par1] x[,par1] if (par2 == 'none') { m <- ctree(as.formula(paste(colnames(x)[par1],' ~ .',sep='')),data = x) } load(file='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='mytable3.tab') } } m bitmap(file='test1.png') plot(m) dev.off() bitmap(file='test1a.png') plot(x[,par1] ~ as.factor(where(m)),main='Response by Terminal Node',xlab='Terminal Node',ylab='Response') dev.off() 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) } bitmap(file='test2.png') 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() 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$Residuals)^2)),4)) a<-table.row.end(a) a<-table.end(a) table.save(a,file='mytable1.tab') a<-table.start() a<-table.row.start(a) a<-table.element(a,'Actuals, Predictions, and Residuals',4,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'#',header=TRUE) a<-table.element(a,'Actuals',header=TRUE) a<-table.element(a,'Forecasts',header=TRUE) a<-table.element(a,'Residuals',header=TRUE) a<-table.row.end(a) for (i in 1:length(result$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='mytable.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='mytable2.tab') }

Copyright

This work is licensed under a Creative Commons Attribution-Noncommercial-Share Alike 3.0 License.

Software written by Ed van Stee & Patrick Wessa

Disclaimer

Information provided on this web site is provided "AS IS" without warranty of any kind, either express or implied, including, without limitation, warranties of merchantability, fitness for a particular purpose, and noninfringement. We use reasonable efforts to include accurate and timely information and periodically update the information, and software without notice. However, we make no warranties or representations as to the accuracy or completeness of such information (or software), and we assume no liability or responsibility for errors or omissions in the content of this web site, or any software bugs in online applications. Your use of this web site is AT YOUR OWN RISK. Under no circumstances and under no legal theory shall we be liable to you or any other person for any direct, indirect, special, incidental, exemplary, or consequential damages arising from your access to, or use of, this web site.

Privacy Policy

We may request personal information to be submitted to our servers in order to be able to:

• personalize online software applications according to your needs
• enforce strict security rules with respect to the data that you upload (e.g. statistical data)
• manage user sessions of online applications
• alert you about important changes or upgrades in resources or applications

We NEVER allow other companies to directly offer registered users information about their products and services. Banner references and hyperlinks of third parties NEVER contain any personal data of the visitor.

We do NOT sell, nor transmit by any means, personal information, nor statistical data series uploaded by you to third parties.

We carefully protect your data from loss, misuse, alteration, and destruction. However, at any time, and under any circumstance you are solely responsible for managing your passwords, and keeping them secret.

We store a unique ANONYMOUS USER ID in the form of a small 'Cookie' on your computer. This allows us to track your progress when using this website which is necessary to create state-dependent features. The cookie is used for NO OTHER PURPOSE. At any time you may opt to disallow cookies from this website - this will not affect other features of this website.

We examine cookies that are used by third-parties (banner and online ads) very closely: abuse from third-parties automatically results in termination of the advertising contract without refund. We have very good reason to believe that the cookies that are produced by third parties (banner ads) do NOT cause any privacy or security risk.

FreeStatistics.org is safe. There is no need to download any software to use the applications and services contained in this website. Hence, your system's security is not compromised by their use, and your personal data - other than data you submit in the account application form, and the user-agent information that is transmitted by your browser - is never transmitted to our servers.

As a general rule, we do not log on-line behavior of individuals (other than normal logging of webserver 'hits'). However, in cases of abuse, hacking, unauthorized access, Denial of Service attacks, illegal copying, hotlinking, non-compliance with international webstandards (such as robots.txt), or any other harmful behavior, our system engineers are empowered to log, track, identify, publish, and ban misbehaving individuals - even if this leads to ban entire blocks of IP addresses, or disclosing user's identity.

FreeStatistics.org is powered by