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A topological method for reduction in digital information uncertainty

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Abstract

An attribute reduct, an important concept of rough set theory, is a subset that is sufficient and individually necessary for preserving a particular property of the given information system. In this study, we present a proposed method to calculate the accuracy of data by using the concepts of pre-open and semi-open. We also compared the results of accuracies in the proposed method with the accuracies in Yao and Pawlak methods. Our study revealed that the new model calculating the degree of accuracy was better than the previous models. Additionally, we provided a new insight into the application of the attribute reduction and we used MATLAB programming to obtain the result.

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Correspondence to M. A. Elsafty.

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This article does not contain any studies with human participants or animals performed by the author. All authors have read the manuscript and agreed to its submission.

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Communicated by V. Loia.

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Appendix

Appendix

See Tables 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20 and 21.

Table 7 After coding information data
Table 8 Discretion of Table 2
Table 9 Removing Attributes
Table 10 Superfluous data
Table 11 Classification data
Table 12 Accuracies for E2
Table 13 Accuracy with proposed method for E2
Table 14 Accuracies for E5
Table 15 Accuracy with proposed method for E5
Table 16 Accuracies for E6
Table 17 Accuracy with proposed method for E6
Table 18 Accuracies for E2 and E5
Table 19 Accuracy with proposed method for E2 and E5
Table 20 Accuracies for E2, E5 and E6
Table 21 Accuracy with proposed method for E2, E5 and E6

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Elsafty, M.A., Alkhathami, A.M. A topological method for reduction in digital information uncertainty. Soft Comput 24, 385–396 (2020). https://doi.org/10.1007/s00500-019-03920-9

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  • DOI: https://doi.org/10.1007/s00500-019-03920-9

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