Use factor indeed as.factor:
factor(x, levels = c('yes', 'no'))
On Thu, Jun 17, 2010 at 4:47 PM, Noah Silverman <n...@smartmediacorp.com>wrote:
> Hi,
>
> I have a dataset where the results are coded ("yes", "no") We want to
> do some machine learning with SVM to predict the "yes" outcome
>
> My problem is that if I just use the as.factor function to convert, then
> it reverses the levels.
>
> ----------------------
> x <- c("no", "no", "no", "yes", "yes", "no", "no")
> as.factor(x)
> [1] no no no yes yes no no
> Levels: no yes
> ----------------------
> The SVM function (in the e1071 package) sees "no" as the first label and
> treats that as the positive outcome. The problem arises when we look at
> the decision values of the
> predictions. Everything is gauged as values for "no".
> So, is there a way to force R to use my specified order when converting
> to factors?
> I've tried as.factor(x, levels=c("yes", "no")) but that throws errors
> about unused arguments.
>
> Any help?
>
>
> Thanks
>
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--
Henrique Dallazuanna
Curitiba-Paraná-Brasil
25° 25' 40" S 49° 16' 22" O
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