@article{MAKHILLIJSC20083420936,
    title = {Reduct Based Decision Tree (RDT)},
    journal = {International Journal of Soft Computing},
    volume = {3},
    number = {4},
    pages = {321-325},
    year = {2008},
    issn = {1816-9503},
    doi = {ijscomp.2008.321.325},
    url = {https://makhillpublications.co/view-article.php?issn=1816-9503&doi=ijscomp.2008.321.325},
    author = {Ramadevi Yellasiri,C.R. Rao,Hari RamaKrishna and},
    keywords = {Rough sets,predominant attributes,composite reduct,RDT,GPCR},
    abstract = {New approaches to compute predominant attributes (referred as reduct) are discussed in this study. Rough Sets concepts and &#8216;val&#8217; theory are adopted in this process. Procedure to construct a decision tree using these reduct is presented. These trees are referred as Reduct based Decision Tree (RDT). Decision rules for these RDTs are generated. &#8216;Kappa statistics&#8217; was used to prove the efficiency of this model which is supported by K-fold test.}
    }