Hi,
On Jul 31, 2009, at 7:17 PM, Noah Silverman wrote:
Hello,
I'm trying to duplicate what's an easy process in RapidMiner.
In RM, we can simply use two operators:
subgroup iteration
attribute value selection (Can use a regex for the attrribute
name.)
I can do this in R with a lot of code and manual steps. It would be
really nice to find a more automated way.
My data looks like this
group group_height group_weight height weight
g22 3.2 8.896 3.2 8.896
g22 2.5 6.95 2.5 6.95
g22 3.1 8.618 3.1 8.618
g49 2.4 6.672 2.4 6.672
g49 4.2 11.676 4.2 11.676
g49 2.5 6.95 2.5 6.95
g55 2.6 7.228 2.6 7.228
g55 3.4 9.452 3.4 9.452
g55 3.3 9.174 3.3 9.174
What I want to do is scale the data by each group
So in pseudo-code
for(group in groups){
if(column_name = regex(group_.*)){
data[column_name] = scale(data[group,column_name])
}
}
This way I get "group wise" normalization of my data, but still have
the
original values which I will normailze "database wide" for some
comparisons.
Can anybody help solve this one?
-N
You can do this quite easily.
Just take what you learned from the last example re: scaling subsets,
and play around with some of the functions you see in the ?grep help
page. You'll be using those functions against the strings you get back
from colnames(data).
-steve
--
Steve Lianoglou
Graduate Student: Computational Systems Biology
| Memorial Sloan-Kettering Cancer Center
| Weill Medical College of Cornell University
Contact Info: http://cbio.mskcc.org/~lianos/contact
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