Abstract
Rough sets theory has taken an important role in data mining. This paper introduces a new rough set based classification rule generation algorithm. It has three features: the first is that the new algorithm can be used in inconsistent systems. The second is its ability to calculate the core value without attributes reduction before. The third is that every example gives a rule and the core values are added first in rule generation process. Experimental results indicate that the classification performanceismuch better than the standard rough set, its variants andJRIPPER, a little better thanCBA and KNN,andcompetive to C4.5in terms of 8 measures. The higher performance of the new algorithm may get benefit from its enough higher accuracy rules and having some properties like KNN.
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Feng, H. et al. (2014). A New Rough Set Based Classification Rule Generation Algorithm(RGA). In: Ali, M., Pan, JS., Chen, SM., Horng, MF. (eds) Modern Advances in Applied Intelligence. IEA/AIE 2014. Lecture Notes in Computer Science(), vol 8481. Springer, Cham. https://doi.org/10.1007/978-3-319-07455-9_39
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DOI: https://doi.org/10.1007/978-3-319-07455-9_39
Publisher Name: Springer, Cham
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