On Influence of Representations of Discretized Data on Performance of a Decision System

When discretization is used for preprocessing datasets in a decision system different representations of data can be taken into consideration. Typical approach is to use data as it is returned by discretizer, namely as nominal values. But in specific cases such form of data cannot be utilized by next modules of the decision system. Then the possible solution is to convert nominal data again into a numerical form. The paper presents comparison of such approaches applied for different classifiers in stylometry domain.