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B11A,regression tree,steven,coomans,thesis,per2maand

*Unverified author*

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

Title produced by software: Recursive Partitioning (Regression Trees)

Date of computation: Wed, 26 May 2010 11:15:05 +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/May/26/t1274872588la75qkrtvvqwp9b.htm/, Retrieved Wed, 26 May 2010 13:16:29 +0200

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/May/26/t1274872588la75qkrtvvqwp9b.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:

B11A,regression tree,steven,coomans,thesis,per2maand

Dataseries X:

» Textbox « » Textfile « » CSV «

46 NA 34.4268537070987 45.95244183468 31 40.5 46 32.4378603466732 40.45638364361 50 22.5 45.45 30.492240334061 22.4728254462900 20 25 43.155 28.5853543104307 24.9687672592201 30 22.25 41.3395 26.7195658658305 22.2199590695251 29 7 39.43055 24.8931981461802 6.98365087358009 10,25 11 36.187495 23.1020415201185 10.9780926872601 11 50.25 33.6687455 21.3485568619093 50.1872845185651 15,25 16.25 35.32687095 19.6418079270611 16.2197263132451 21 32.5 33.419183855 17.9671794656517 32.4519181330501 15 5.7525 33.3272654695 16.3327560407159 5.72960743135642 30 7.75 30.56978892255 14.7288766581764 7.72355174403519 5,6 14 28.287810030295 13.1590323347601 27.3017308111177 15,6 3.5 26.8590290272655 11.6240545816589 21.8017308111392 10 1.25 24.5231261245390 10.1198715180038 3.80173081107135 0 3.0125 22.1958135120851 8.64677576944595 6.30173081107452 0,5 0.5 20.2774821608766 7.20503203420426 3.5517308110735 0 0 18.2997339447889 5.79327468630679 -11.6982691889900 0 0.875 18.2997339447889 4.41123208898345 -7.69 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	2 seconds
R Server	'RServer@AstonUniversity' @ vre.aston.ac.uk
R Framework error message	Warning: there are blank lines in the 'Data X' field. Please, use NA for missing data - blank lines are simply deleted and are NOT treated as missing values.

Model Performance
#	Complexity	split	relative error	CV error	CV S.D.
1	0.569	0	1	1.067	0.312
2	0.01	1	0.431	0.897	0.227

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/May/26/t1274872588la75qkrtvvqwp9b/1eqj51274872502.png (open in new window)

http://www.freestatistics.org/blog/date/2010/May/26/t1274872588la75qkrtvvqwp9b/1eqj51274872502.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/May/26/t1274872588la75qkrtvvqwp9b/2eqj51274872502.png (open in new window)

http://www.freestatistics.org/blog/date/2010/May/26/t1274872588la75qkrtvvqwp9b/2eqj51274872502.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/May/26/t1274872588la75qkrtvvqwp9b/3eqj51274872502.png (open in new window)

http://www.freestatistics.org/blog/date/2010/May/26/t1274872588la75qkrtvvqwp9b/3eqj51274872502.ps (open in new window)

Parameters (Session):

par1 = 1 ; par2 = No ;

Parameters (R input):

par1 = 1 ; par2 = No ;

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

library(rpart)

library(partykit)

par1 <- as.numeric(par1)

autoprune <- function ( tree, method='Minimum CV'){

xerr <- tree$cptable[,'xerror']

cpmin.id <- which.min(xerr)

if (method == 'Minimum CV Error plus 1 SD'){

xstd <- tree$cptable[,'xstd']

errt <- xerr[cpmin.id] + xstd[cpmin.id]

cpSE1.min <- which.min( errt < xerr )

mycp <- (tree$cptable[,'CP'])[cpSE1.min]

}

if (method == 'Minimum CV') {

mycp <- (tree$cptable[,'CP'])[cpmin.id]

}

return (mycp)

}

conf.multi.mat <- function(true, new)

{

if ( all( is.na(match( levels(true),levels(new) ) )) )

stop ( 'conflict of vector levels')

multi.t <- list()

for (mylev in levels(true) ) {

true.tmp <- true

new.tmp <- new

left.lev <- levels (true.tmp)[- match(mylev,levels(true) ) ]

levels(true.tmp) <- list ( mylev = mylev, all = left.lev )

levels(new.tmp)  <- list ( mylev = mylev, all = left.lev )

curr.t <- conf.mat ( true.tmp , new.tmp )

multi.t[[mylev]] <- curr.t

multi.t[[mylev]]$precision <-

round( curr.t$conf[1,1] / sum( curr.t$conf[1,] ), 2 )

}

return (multi.t)

}

x <- t(y)

k <- length(x[1,])

n <- length(x[,1])

x1 <- cbind(x[,par1], x[,1:k!=par1])

mycolnames <- c(colnames(x)[par1], colnames(x)[1:k!=par1])

colnames(x1) <- mycolnames #colnames(x)[par1]

m <- rpart(as.data.frame(x1))

par2

if (par2 != 'No') {

mincp <- autoprune(m,method=par2)

print(mincp)

m <- prune(m,cp=mincp)

}

m$cptable

bitmap(file='test1.png')

plot(as.party(m),tp_args=list(id=FALSE))

dev.off()

bitmap(file='test2.png')

plotcp(m)

dev.off()

cbind(y=m$y,pred=predict(m),res=residuals(m))

myr <- residuals(m)

myp <- predict(m)

bitmap(file='test4.png')

op <- par(mfrow=c(2,2))

plot(myr,ylab='residuals')

plot(density(myr),main='Residual Kernel Density')

plot(myp,myr,xlab='predicted',ylab='residuals',main='Predicted vs Residuals')

plot(density(myp),main='Prediction Kernel Density')

par(op)

dev.off()

load(file='createtable')

a<-table.start()

a<-table.row.start(a)

a<-table.element(a,'Model Performance',6,TRUE)

a<-table.row.end(a)

a<-table.row.start(a)

a<-table.element(a,'#',header=TRUE)

a<-table.element(a,'Complexity',header=TRUE)

a<-table.element(a,'split',header=TRUE)

a<-table.element(a,'relative error',header=TRUE)

a<-table.element(a,'CV error',header=TRUE)

a<-table.element(a,'CV S.D.',header=TRUE)

a<-table.row.end(a)

for (i in 1:length(m$cptable[,1])) {

a<-table.row.start(a)

a<-table.element(a,i,header=TRUE)

a<-table.element(a,round(m$cptable[i,'CP'],3))

a<-table.element(a,m$cptable[i,'nsplit'])

a<-table.element(a,round(m$cptable[i,'rel error'],3))

a<-table.element(a,round(m$cptable[i,'xerror'],3))

a<-table.element(a,round(m$cptable[i,'xstd'],3))

a<-table.row.end(a)

}

a<-table.end(a)

table.save(a,file='mytable.tab')

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

Software written by Ed van Stee & Patrick Wessa

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