1.School of Computer Science and Technology, Yantai University, Yantai 2640052. School of Computer Engineering and Technology, Shanghai University, Shanghai 200072
Abstract：Several measurements of the discretization schemes for continuous decision tables are discussed, including cut-point number, conditional entropy, granular entropy, class-attribute mutual information and interdependence redundancy. For consistent decision table, conditional entropy and class-attribute mutual information are both constants, and thus they can not offer more information for discretization schemes. The relationship between granular entropy and interdependence redundancy is analyzed. And it is proved that granular entropy increases when new cut points are added to the discretization scheme. A hybrid discretization algorithm is proposed to provide discretization schemes for testing. The simulation results show that the correlation coefficient between the cut-point number and classification accuracy is basically equal to that between granular entropy and classification accuracy, and both of them are correlated to datasets.
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2008, Vol. 21 
