This is very weird. Is this a bug in MASS QDA?
On 3/11/06, Michael <[EMAIL PROTECTED]> wrote:
>
> Yes, I am using the MASS qda... How do I know which version is my MASS? I
> should be using the latest one, since I constantly update my packages from
> mirror site USA CA1.
>
> Very weird!!!
>
> -------------------------------
> Here is my code:
>
>
> rm(list=ls(all=TRUE))
> library(MASS);
>
> temp=as.matrix(read.table('spam.train'));
> temp2=as.matrix(read.table('spam.test'));
>
> #QDA Priors (0.5, 0.5)
> lll <- qda((temp[, -58]), as.factor(temp[, 58]), prior=c(0.2, 0.8));
>
> print('Priors (0.2, 0.8) QDA: Training ... ');
> ttt=predict(lll, temp[, -58])$class;
> cc1=table(temp[, 58], ttt);
> print(cc1);
> dd1=cc1 %*% matrix(1, 2, 1);
> ee1=cc1 / as.vector(dd1);
> print(ee1);
>
>
> print('Priors (0.2, 0.8) QDA: Testing ... ');
> ttt=predict(lll, temp2[, -58])$class;
> cc2=table(temp2[, 58], ttt);
> print(cc2);
> dd2=cc2 %*% matrix(1, 2, 1);
> ee2=cc2 / as.vector(dd2);
> print(ee2);
>
> #QDA Proportional Priors
> lll <- qda((temp[, -58]), as.factor(temp[, 58]));
>
> print('Proportional Priors QDA: Training ... ');
> ttt=predict(lll, temp[, -58])$class;
> cc1=table(temp[, 58], ttt);
> print(cc1);
> dd1=cc1 %*% matrix(1, 2, 1);
> ee1=cc1 / as.vector(dd1);
> print(ee1);
>
>
> print('Proportional Priors QDA: Testing ... ');
> ttt=predict(lll, temp2[, -58])$class;
> cc2=table(temp2[, 58], ttt);
> print(cc2);
> dd2=cc2 %*% matrix(1, 2, 1);
> ee2=cc2 / as.vector(dd2);
> print(ee2);
>
> --------------------------------------------------
>
> Here is the result:
>
>
> [1] "Priors (0.2, 0.8) QDA: Training ... "
> 0 1
> 0 1051 355
> 1 40 855
>
> 0 1
> 0 0.74751067 0.25248933
> 1 0.04469274 0.95530726
>
> [1] "Priors (0.2, 0.8) QDA: Testing ... "
> 0 1
> 0 993 389
> 1 47 871
>
> 0 1
> 0 0.71852388 0.28147612
> 1 0.05119826 0.94880174
>
> [1] "Proportional Priors QDA: Training ... "
> 0 1
> 0 1058 348
> 1 41 854
>
> 0 1
> 0 0.75248933 0.24751067
> 1 0.04581006 0.95418994
>
> [1] "Proportional Priors QDA: Testing ... "
>
> 0 1
> 0 999 383
> 1 47 871
>
> 0 1
> 0 0.72286541 0.27713459
> 1 0.05119826 0.94880174
>
>
>
>
> On 3/11/06, Uwe Ligges <[EMAIL PROTECTED]> wrote:
> >
> > Michael wrote:
> >
> > > Hi all,
> > >
> > > If I run LDA on the same data (2-class classification) with default(no
> >
> > > priors specified in the lda function) vs. "prior=c(0.5, 0.5)", the
> > results
> > > are different.
> > >
> > > The (0.5, 0.5) priors give better 1-classify-to-1 rate, and the
> > proportional
> > > priors(default, no priors specified in the lda function) give better
> > > 0-classify-to-0 rate, for both training and testing data sets.
> > >
> > > However, if I run QDA on the same data (2-class classification) with
> > > default(no priors specified in the lda function) vs. "prior=c( 0.5,
> > 0.5)",
> > > the results are the same,
> > >
> > > i.e. the confusion tables are completely the same for two types of
> > priors, I
> > > even tried "qda" function with "prior=c(0.3, 0.7)" and other values,
> > the
> > > confusion tables are still the same...
> > >
> > > What might be the problem?
> >
> >
> > Are we talking about the lda() and qda() implementations in package
> > MASS?
> > Which versions of R and MASS (?) are we talking about?
> > Can you specify a reproducible example, please?
> >
> > The follwing example works for me:
> > library(MASS)
> > qdaObj <- qda(Species ~ ., data = iris, prior = c(1, 0, 0))
> > predict(qdaObj)$class
> >
> > Uwe Ligges
> >
> >
> >
> >
> > > Thanks a lot!
> > >
> > > [[alternative HTML version deleted]]
> > >
> > > ______________________________________________
> > > 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<http://www.r-project.org/posting-guide.html>
> >
> >
>
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