Abstract
In this paper, we present an extended technique of decision making by implementing column reduction with reduction based on calculated maximal support objects. Using a Boolean valued information system, certain rows or objects can be defined as ultimate maximum support object, ultimate minimum support object and zero significance parameter. One can then reduce a table by eliminating the defined row or objects in what has been defined as hybrid reduction. As part of our paper, we have managed to show that our proposed model of hybrid reduction yielded a better data size reduction whilst still maintaining consistent results.
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Rose, A.N.M., Awang, M.I., Hassan, H., Zakaria, A.H., Herawan, T., Deris, M.M. (2011). Hybrid Reduction in Soft Set Decision Making. In: Huang, DS., Gan, Y., Bevilacqua, V., Figueroa, J.C. (eds) Advanced Intelligent Computing. ICIC 2011. Lecture Notes in Computer Science, vol 6838. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24728-6_15
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DOI: https://doi.org/10.1007/978-3-642-24728-6_15
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-24727-9
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