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# Nominal variable= dummy-coded variable?

Was wondering about this the other day. If I select a variable to be nominal, and it has X categories, is this mathematically equal to having manually edited the variable into n-1 (or n) dummy categories?

That is, if I use a method that accepts inputs of nominal measures, is there any difference if the nominal variable has been split into a group of binomial variables or not?

-Frankie

That is, if I use a method that accepts inputs of nominal measures, is there any difference if the nominal variable has been split into a group of binomial variables or not?

-Frankie

0

## Answers

537MavenTheoretically you just need log_2(k).

The k-1 is used in ANOVA, ANCOVA, Generalised Linear Models, etc.

Either coded 1/0 (dummy coding), or 1/-1 (effect coding).

Please read:

www.cs.washington.edu/homes/jbigham/cv/princeton-thesis.pdf

On Using Error-Correcting Codes and Boosting to Learn Multi-Class Classification Problems

Error-Correcting Codes is a very important keyword.

26Contributor IITo clarify a bit more though. What I meant by my question... will RM do these conversion to dummy variables in the background when the nominal-type has been chosen?

537Maven26Contributor II537MavenSo if you use for example the algorithm ID3, it does not make dummies at all, it calculates information gain directly on the original attributes.

2,531UnicornRapidMiner does not transform any nominal typed variables to numerical ones if the learner does need this! We are sticking to the believe that the user should be in full control over what the process does.

In fact it would be easy adding this, but since the dummy encoding of nominal variables can have a major impact on the (prediction) performance, we won't do this implicitly. Instead we are presenting the user QuickFixes with which the user is capable of solving the problem with one click.

Greetings,

Â Sebastian