Solving incomplete datasets in soft set using supported sets and aggregate values
The theory of soft set proposed by Molodtsovin 1999[1]is a new method for handling uncertain data and can be defined as a Boolean-valued information system. Ithas been applied to data analysis and decision support systems based on large datasets. In this paper, it is shown that calculated support...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Published: |
Elsevier Ltd.
2011
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| Subjects: | |
| Online Access: | http://eprints.uthm.edu.my/2979/ |
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| Summary: | The theory of soft set proposed by Molodtsovin 1999[1]is a new method for handling uncertain data and can be
defined as a Boolean-valued information system. Ithas been applied to data analysis and decision support systems
based on large datasets. In this paper, it is shown that calculated support value can be used to determine missing
attribute value of an object. However, in cases when more than one value is missing, the aggregate values and
calculated support values will be used in determining the missing values. By successfully recovering missing
attribute values, the integrity of a dataset can still been maintained. |
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