Home » date » 2010 » May » 26 »

B511,regression tree,per maand,steven,coomans,thesis

*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 10:13:29 +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/t1274868877jrb5kh90sz4daa0.htm/, Retrieved Wed, 26 May 2010 12:14:37 +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/t1274868877jrb5kh90sz4daa0.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:

B511,regression tree,per maand,steven,coomans,thesis

Dataseries X:

» Textbox « » Textfile « » CSV «

66 NA 66.6400081602945 65.9340000642625 66 66 66 74.8865290244873 65.9999544970003 44 66 66 69.4466779638461 65.9999741429027 66 76 66 54.592968576561 67.2912652912436 88 34 67 65.359813335731 65.097618300786 66 66 63.7 53.5306148746235 61.2705546832229 67 66 63.93 60.2131403294856 62.1803867658173 66 66 64.137 81.3710894221322 62.85982112799 66 66 64.3233 54.1503901382023 63.3873521146392 44 66 64.49097 63.170927562093 63.8082659858302 66 44 64.641873 53.4785961678077 62.7780896791892 44 44 62.5776857 36.0086271515583 59.9095531527368 44 66 60.71991713 65.3413647125152 59.6936234581407 44 87.5 61.247925417 73.8332331092841 60.8356206794414 66 66 63.8731328753 72.6698371634263 64.5842558764913 NA 66 64.08581958777 57.2076479997321 67.8930159267455 66 66 64.277237628993 65.5773520419694 54.5864341559968 66 65.5 64.4495138660937 59.7783847805255 66.1702603554484 88 65.5 64.5545624794843 65.1808994846169 66.0732597482336 66 88 64.6491062315359 85.3000011788247 66.1506824734975 66 42 66.984195 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	3 seconds
R Server	'Sir Ronald Aylmer Fisher' @ 193.190.124.24
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	0.391	0	1	1.028	0.191
2	0.114	1	0.609	0.834	0.155
3	0.052	2	0.495	0.708	0.167
4	0.01	3	0.444	0.765	0.177

Charts produced by software:

http://www.freestatistics.org/blog/date/2010/May/26/t1274868877jrb5kh90sz4daa0/1ka3l1274868805.png (open in new window)

http://www.freestatistics.org/blog/date/2010/May/26/t1274868877jrb5kh90sz4daa0/1ka3l1274868805.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/May/26/t1274868877jrb5kh90sz4daa0/2ka3l1274868805.png (open in new window)

http://www.freestatistics.org/blog/date/2010/May/26/t1274868877jrb5kh90sz4daa0/2ka3l1274868805.ps (open in new window)

http://www.freestatistics.org/blog/date/2010/May/26/t1274868877jrb5kh90sz4daa0/3ka3l1274868805.png (open in new window)

http://www.freestatistics.org/blog/date/2010/May/26/t1274868877jrb5kh90sz4daa0/3ka3l1274868805.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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