Re: [R] confusion matrix - better code?
Wolfgang,
This looks great and certainly puts to shame my code .
Thanks,
Monica
Date: Fri, 7 Sep 2007 21:04:32 +0100 From: [EMAIL PROTECTED] To: [EMAIL
PROTECTED] CC: r-help@stat.math.ethz.ch Subject: Re: [R] confusion matrix -
better code? Dear Monica, try this: cm = table(tr, pr) cm pr tr 1
2 3 1 2 1 0 2 2 1 0 3 0 0 3 4 0 1 0 rowSums(cm) colSums(cm) Best
wishes Wolfgang Huber Monica Pisica ha scritto: Hi,I�ve
written some code to obtain a confusion matrix when the true classification
and the predicted classification are known. Suppose true classification is
called �tr� and predicted classification is �pr�. I have 4 classes in
tr, but only 3 classes out of 4 are predicted in �pr�. Following is my
code, but looks quite �clunky� to me. I wonder if you have any
suggestions to improve it.Thanks,Monica
-tr - c(1,2,2,3,3,3,2,4,1,1)
pr-c(1,2,1,3,3,3,1,2,1,2) dat - data.frame(tr, pr) class -
c(1:length(tr)) m - max(c(length(unique(tr)), length(unique(pr
for(i in 1:length(class)) { class[i] - sub('
','',paste(dat[i,1],dat[i,2])) } dat - data.frame(dat, class) mat -
matrix(0, nrow=m, ncol=m) for (i in 1:m){ for (j in 1:m){ mat[i,j]
- sub(' ','',paste(i,j)) }} cat - matrix(0, nrow=(m+1), ncol=(m+1))
for (i in 1:m){ for(j in 1:m){ cat[i,j]-
nrow(dat[dat$class==mat[i,j],]) }} for (i in 1:m){
cat[(m+1),i]-sum(cat[1:m,i]) cat[i,(m+1)]- sum(cat[i,1:m])
cat[(m+1),(m+1)] - sum(cat[1:m,(m+1)]) } cat [,1] [,2] [,3] [,4]
[,5] [1,] 2 1 0 0 3 [2,] 2 1 0 0 3 [3,] 0 0 3 0 3 [4,] 0 1 0 0 1
[5,] 4 3 3 0 10The 5th row / col represents the sum on each row /
col respectively.
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Re: [R] confusion matrix - better code?
Michael,
Thank you very much. My code is certainly put to shame by yours. I promise to
read about factor to see how you use it and why ;-))
I really appreciate your help.
Monica
Subject: RE: [R] confusion matrix - better code? Date: Fri, 7 Sep 2007
15:36:00 -0500 From: [EMAIL PROTECTED] To: [EMAIL PROTECTED] How about
this?
tab-table(factor(tr,levels=unique(tr)),factor(pr,levels=unique(tr)))
tab-rbind(tab,colSums(tab)) tab-cbind(tab,rowSums(tab)) tab 1 2 3 4
1 2 1 0 0 3 2 2 1 0 0 3 3 0 0 3 0 3 4 0 1 0 0 1 4 3 3 0 10 Of
course you can add some dimnames for the 5th row and 5th column if you
want. dimnames(tab)[[1]][5]-Total dimnames(tab)[[2]][5]-Total
tab 1 2 3 4 Total 1 2 1 0 0 3 2 2 1 0 0 3 3 0 0 3 0 3 4 0 1 0 0 1 Total
4 3 3 0 10 Michael Conklin Chief Methodologist - Advanced Analytics
MarketTools, Inc. 6465 Wayzata Blvd. Suite 170 Minneapolis, MN
55426 Tel: 952.417.4719 | Mobile:612.201.8978 [EMAIL PROTECTED]
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From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] On Behalf Of Monica
Pisica Sent: Friday, September 07, 2007 2:53 PM To:
r-help@stat.math.ethz.ch Subject: [R] confusion matrix - better code?
Importance: High Hi, I've written some code to obtain a confusion
matrix when the true classification and the predicted classification are
known. Suppose true classification is called tr and predicted
classification is pr. I have 4 classes in tr, but only 3 classes out of 4
are predicted in pr. Following is my code, but looks quite clunky to me.
I wonder if you have any suggestions to improve it. Thanks, Monica
- tr - c(1,2,2,3,3,3,2,4,1,1)
pr-c(1,2,1,3,3,3,1,2,1,2) dat - data.frame(tr, pr) class -
c(1:length(tr)) m - max(c(length(unique(tr)), length(unique(pr for(i
in 1:length(class)) { class[i] - sub(' ','',paste(dat[i,1],dat[i,2])) }
dat - data.frame(dat, class) mat - matrix(0, nrow=m, ncol=m) for (i in
1:m){ for (j in 1:m){ mat[i,j] - sub(' ','',paste(i,j)) }} cat -
matrix(0, nrow=(m+1), ncol=(m+1)) for (i in 1:m){ for(j in 1:m){
cat[i,j]- nrow(dat[dat$class==mat[i,j],]) }} for (i in 1:m){
cat[(m+1),i]-sum(cat[1:m,i]) cat[i,(m+1)]- sum(cat[i,1:m])
cat[(m+1),(m+1)] - sum(cat[1:m,(m+1)]) } cat [,1] [,2] [,3] [,4] [,5]
[1,] 2 1 0 0 3 [2,] 2 1 0 0 3 [3,] 0 0 3 0 3 [4,] 0 1 0 0 1 [5,] 4 3 3 0
10 The 5th row / col represents the sum on each row / col respectively.
_ Gear up
for Halo(r) 3 with free downloads and an exclusive offer. It's our way of
saying thanks for using Windows Live(tm). [[alternative HTML version
deleted]]
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é.
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[R] confusion matrix - better code?
Hi,
Ive written some code to obtain a confusion matrix when the true
classification and the predicted classification are known. Suppose true
classification is called tr and predicted classification is pr. I have 4
classes in tr, but only 3 classes out of 4 are predicted in pr. Following is
my code, but looks quite clunky to me. I wonder if you have any suggestions
to improve it.
Thanks,
Monica
-
tr - c(1,2,2,3,3,3,2,4,1,1)
pr-c(1,2,1,3,3,3,1,2,1,2)
dat - data.frame(tr, pr)
class - c(1:length(tr))
m - max(c(length(unique(tr)), length(unique(pr
for(i in 1:length(class)) {
class[i] - sub(' ','',paste(dat[i,1],dat[i,2])) }
dat - data.frame(dat, class)
mat - matrix(0, nrow=m, ncol=m)
for (i in 1:m){
for (j in 1:m){
mat[i,j] - sub(' ','',paste(i,j))
}}
cat - matrix(0, nrow=(m+1), ncol=(m+1))
for (i in 1:m){
for(j in 1:m){
cat[i,j]- nrow(dat[dat$class==mat[i,j],])
}}
for (i in 1:m){
cat[(m+1),i]-sum(cat[1:m,i])
cat[i,(m+1)]- sum(cat[i,1:m])
cat[(m+1),(m+1)] - sum(cat[1:m,(m+1)])
}
cat
[,1] [,2] [,3] [,4] [,5]
[1,]21003
[2,]21003
[3,]00303
[4,]01001
[5,]4330 10
The 5th row / col represents the sum on each row / col respectively.
_
Gear up for Halo® 3 with free downloads and an exclusive offer. Its our way of
saying thanks for using Windows Live.
[[alternative HTML version deleted]]
__
R-help@stat.math.ethz.ch mailing list
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PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
Re: [R] confusion matrix - better code?
Dear Monica,
try this:
cm = table(tr, pr)
cm
pr
tr 1 2 3
1 2 1 0
2 2 1 0
3 0 0 3
4 0 1 0
rowSums(cm)
colSums(cm)
Best wishes
Wolfgang Huber
Monica Pisica ha scritto:
Hi,
I�ve written some code to obtain a confusion matrix when the true
classification and the predicted classification are known. Suppose true
classification is called �tr� and predicted classification is �pr�. I have 4
classes in tr, but only 3 classes out of 4 are predicted in �pr�. Following
is my code, but looks quite �clunky� to me. I wonder if you have any
suggestions to improve it.
Thanks,
Monica
-
tr - c(1,2,2,3,3,3,2,4,1,1)
pr-c(1,2,1,3,3,3,1,2,1,2)
dat - data.frame(tr, pr)
class - c(1:length(tr))
m - max(c(length(unique(tr)), length(unique(pr
for(i in 1:length(class)) {
class[i] - sub(' ','',paste(dat[i,1],dat[i,2])) }
dat - data.frame(dat, class)
mat - matrix(0, nrow=m, ncol=m)
for (i in 1:m){
for (j in 1:m){
mat[i,j] - sub(' ','',paste(i,j))
}}
cat - matrix(0, nrow=(m+1), ncol=(m+1))
for (i in 1:m){
for(j in 1:m){
cat[i,j]- nrow(dat[dat$class==mat[i,j],])
}}
for (i in 1:m){
cat[(m+1),i]-sum(cat[1:m,i])
cat[i,(m+1)]- sum(cat[i,1:m])
cat[(m+1),(m+1)] - sum(cat[1:m,(m+1)])
}
cat
[,1] [,2] [,3] [,4] [,5]
[1,]21003
[2,]21003
[3,]00303
[4,]01001
[5,]4330 10
The 5th row / col represents the sum on each row / col respectively.
__
R-help@stat.math.ethz.ch mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
