Hi,
Thanks for the tip,
Neither method works as my data is truly nominal
-------------------------------------
foo <- c("blue", "red", "green")
as.numeric(foo)
[1] NA NA NA
Warning message:
NAs introduced by coercion
------------------------------------
Rapid Miner has a function that will automatically create an "index" of
the values and create a new variable (or replace the existing). It also
has a second function that will break the nominal labels into n variable
that are binary:
i.e.
red(0,1)
blue(0,1)
green(0,1)
Or, I guess I could go back to the source that generates my data and
institute a numeric key for the nominal items. That seems like the
longest way, but probably the safest to get what I want.
-N
On 8/12/09 9:10 AM, Phil Spector wrote:
It's generally safer to use
as.numeric(as.character(variablename))
since it eliminates problems associated with factors.
- Phil Spector
Statistical Computing Facility
Department of Statistics
UC Berkeley
spec...@stat.berkeley.edu
On Wed, 12 Aug 2009, Daniel Malter wrote:
Hi you can use newvariable=as.numeric(variablename). This converts your
factors into numeric variables, but not always with the desired
result. So
make sure that you check whether "newvariable" gives you what you want.
Otherwise recoding by hand is indicated.
Best,
Daniel
Noah Silverman-3 wrote:
Hi,
I'm training an SVM (C-classification from e1071 library)
Some of the variables in my data set are nominal. Is there some
easy/automatic way to convert them to numerical representations?
Thanks,
-N
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