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Classification of Rank for Distributors of Multi-Level Marketing Company by Using Decision Tree Induction

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dc.contributor.author Aung, Htet Htet
dc.contributor.author Yee, Myint Myint
dc.date.accessioned 2019-10-15T16:08:56Z
dc.date.available 2019-10-15T16:08:56Z
dc.date.issued 2019-03
dc.identifier.uri http://onlineresource.ucsy.edu.mm/handle/123456789/2296
dc.description.abstract Data Mining is a step in the knowledge discovery process consisting of particular data mining algorithms that, under some acceptable computational efficiency limitations, find patterns or models in data [1]. Classification and prediction are two forms of data analysis that can be used to extract models describing important data classes or to predict future data trends. Decision tree is commonly used for the gaining information for the purpose of decision making. This paper intends to apply the Decision tree induction ID3 algorithm on the distributor’s performance data to generate the classification model and this model can be used to predict the promotion of rank for the distributors. The dataset is used from ZhulianMulti-level Marketing Company. 10-fold Cross Validation accuracy method is used to approve the system accuracy. en_US
dc.language.iso en_US en_US
dc.publisher National Journal of Parallel and Soft Computing en_US
dc.relation.ispartofseries Vol-1, Issue-1;
dc.subject data mining en_US
dc.subject classification en_US
dc.subject decision tree en_US
dc.subject ID3 algorithm en_US
dc.subject K-fold Cross Validation accuracy method en_US
dc.title Classification of Rank for Distributors of Multi-Level Marketing Company by Using Decision Tree Induction en_US
dc.type Article en_US


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