What is it all about ?

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·  Nominal variables can only have symbolic values, that cannot be ordered with respect to a greaterless relation. An example for a nominal variable is the color of an object, which can have the different symbols red, green and blue.


·  Ordinal variables can only have symbolic values, but, in contrast to nominal variables, they can be ordered with respect to a greaterless relation. An example for an ordinal variable is a temperature that is measured with the qualitative terms cold, normal, warm and hot. Another example is the age of a person that is measured in years. Within the PNC2 Rule Induction System, ordinal variables with just a few different symbols, as the above example with the temperature, are treated as nominal. But ordinal variables with many different symbols, as the above example with the age, are treated as continuous.


·  Continuous variables can have arbitrary real values  only limited by the precision of the measuring device. An example for a continuous variable is the temperature measured in centigrade.


·  Classification tasks

Mean classification error (MCE), i.e. the mean number of missclassifications done


·  Regression tasks

Mean absolute error (MAE)

