Classifying an Object using Class Differentiators


  • Seunghyun Im University of Pittsburgh at Johnstown
  • Li-Shiang Tsay North Carolina A&T University



Classification algorithm, Supervised Classifier, Categorical Data, Reduct, Rough Set


This paper discusses a supervised classification method. The method classifies an object using class differentiators. The class differentiators are the smallest set of values in a class that effectively distinguish one class from the others. The class membership is determined by the degree of homology between the test object and the class differentiators. Unlike many rule based classifiers, the algorithm proposed in this paper does not require input parameters and always produces the same results from the same data set. The algorithm is designed to work with categorical data, and is particularly useful when the quantification of the data is infeasible. We present an experimental result to show the validity of the algorithm.


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How to Cite

Im, S., & Tsay, L.-S. (2014). Classifying an Object using Class Differentiators. Transactions on Engineering and Computing Sciences, 2(5), 64–71.