A function to learn a rule in case of 2 classes or more. There are reduction dimension methods (accessible via argument procedure) to make the procedure efficient when the number of features is larger than the number of observations
1 2 
The Argument are exactly the same as in learnBinaryRule
except that y may have more than 2 levels
x 
see 
y 
vector of factors with two or more levels 
type 

procedure 

ql 

qq 

BinaryLearningProcedure 

prior 
Do we put a prior on y (taking into account the proportion of the different class in the learning set to build the classification rule 
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