General settings
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The general settings of the parameter tuning can be edited on the tab sheet Basic. 



Setting
Explanation
note
Estimation method for the
prediction accuracy


·N-fold repetition  
Requires additionally the specification of the data splitting used to divide the learn data sample into tuning learn and test data samples.  
·N-fold cross-validation  
·Leave-one-out cross-validation (LOOCV)  


note
Skipping
Skip parameter sets, if the resulting model size will exceed the maximum size or the minimum compression thresholds


note
Maximum size

Maximum model size relative to the number of tuning learn data tuples


note
Min. compression   

Maximum model size relative to the number of tuning learn data tuples without elimination of rules with a small mass


note
Randomize

Initialize the random number generator.

Hint: Sometimes it is quite useful to turn this off, if you want to have reproducible results.

 
 
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