Dear Dhruv,
You could create interaction variables manually (assuming A is your
dependent variable). Just multiply the variables together.
cd.int<-C*D
ce.int<-C*E
cde.int<-C*D*E # what about D*E, or interactions with B?
Include those in your model, such as A~B+C+D+E+cd.int+cd.int+ce.int+cde.int.
Then you can compare those models to the results you get when you specify
the interaction in the model formula directly using the documented syntax.
In your R-console, type ?formula, or help("formula") for details.
Sincerely,
KeithC.
-----Original Message-----
From: Sharma, Dhruv [mailto:dhruv.sha...@penfed.org]
Sent: Saturday, March 06, 2010 10:30 AM
To: r-help@r-project.org
Subject: [R] r code to generate interaction columns
Hi,
is there a way to take a dataset and extract numeric columns and create
interaction columns from it automatically?
For e.g. there are 5 columns of data: A,B,C,D,E.
CDE are numeric.
Can someone provide code to automatically create more columns such as:
1) C*D, C*E, C*D*E, (C+E)/(D+.01 (to avoid divide by zero), (D+E)/(C+.01
(to avoid divide by zero), (C+D)/(E+.01 (to avoid divide by zero))
?
I know in glm multiplying can create terms but i want the columns to be part
of the data set so that i can feed this into Random forest to pick out
predictive interaction terms as regression cannot reliably handle correlated
interaction terms.
if anyone has some simple code that can do this that would be helpful.
thanks
Dhruv
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