A Multi-Valued Attribute and Multi-Labeled Data Decision Tree Algorithm
Chen Song · 2007
Multi-valued and multi-labeled classifier(MMC)and multi-valued and multi-labeled decision tree(MMDT)are two existing decision tree algorithms for dealing with multi-valued and multi- labeled data.Based on the two algorithms,formula sim_3 is put forward to calculate the similarity between two label sets.By amending the measuring formula of same-based similarity of label-sets in MMDT,a new decision tree algorithm,similarity of same and consistent in constructing same in predicting(SCC_SP)is proposed with comprehensive consideration of both similarity and appropriateness of the label set.Results of contrast experiments with the same prediction mechanism show that SCC_SP has higher accuracy rate than MMDT.