One-RM: An Improved One-Rule Classifier

Authors

  • Abdur Mahmood University of Dhaka, Dhaka-1000, Bangladesh
  • Wei Lei University of Melbourne, Australia

DOI:

https://doi.org/10.3329/bjsir.v44i2.3668

Keywords:

One-RM, One-R algorithm, Algorithm, Accuracy and Complexity

Abstract

One-R algorithm is a simple algorithm which exhibits quite good predictive accuracy for a large class of data. When compared to the more complex algorithms having better predictive accuracy, One-R provides the baseline accuracy for testing new machine learning algorithms. However, the simplicity of One-R means that it has there is a compromise between accuracy and complexity. Often, the accuracy of One- R can be further increased without making it significantly complex. The resulting algorithm as proposed in this paper, One-RM performs equal to One-R in most of the cases and sometimes outperforms One-R by significant margin. Theoretical analysis suggests that One-RM used in conjunction with One-R always performs either better or equal to One-R. Experimental analysis shows that One-RM is a viable alternative to One-R when used as a separate classification rule.

Key words: One-RM, One-R algorithm, Algorithm, Accuracy and Complexity.

DOI: 10.3329/bjsir.v44i2.3668

Bangladesh J. Sci. Ind. Res. 44(2), 171-180, 2009

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How to Cite

Mahmood, A., & Lei, W. (2009). One-RM: An Improved One-Rule Classifier. Bangladesh Journal of Scientific and Industrial Research, 44(2), 171–180. https://doi.org/10.3329/bjsir.v44i2.3668

Issue

Vol. 44 No. 2 (2009)

Section

Articles

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