Perhaps:
for(i in 1:100)assign(sprintf("Informative.data.class%s", i),
rnorm(100, 0.25,1))
for(i in 1:100)assign(sprintf("Uninformative.data.class%s", i), rnorm(900))
Or working with a list:
Informative <- replicate(100, rnorm(100, 0.25,1))
Uninformative <- replicate(100, rnorm(900))
On 06/02/2008, Nair, Murlidharan T <[EMAIL PROTECTED]> wrote:
> I am trying to generate artificial data for feature selection. Basically
> trying to generate a total of 1000 features with 100 that are informative and
> rest are uninformative.
> Informative.data.class1<-rnorm(100,0.25,1)
> Uninformative.data.class1<-rnorm(900,0,1)
> Informative.data.class2<-rnorm(100, -0.25,1)
> Uninformative.data.class2<-rnorm(900,0,1)
>
> The above will give me one set of data for the two classes. I am interested
> in generating about a 100 set for each class. What is a neat way to write it
> in R?
> Thanks ../Murli
>
>
> [[alternative HTML version deleted]]
>
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--
Henrique Dallazuanna
Curitiba-Paraná-Brasil
25° 25' 40" S 49° 16' 22" O
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