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:
> [email protected]> 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.>
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é.
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