Approximate Accuracy Approaches to Attribute Reduction for Information Systems
The key problem for attribute reduction to information systems is how to evaluate the importance of an attribute. The algorithms are challenged by the variety of data forms in information system. Based on rough sets theory we present a new approach to attribute reduction for incomplete information s...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2014-01-01
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| Series: | Abstract and Applied Analysis |
| Online Access: | http://dx.doi.org/10.1155/2014/382967 |
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| _version_ | 1832563278380793856 |
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| author | Deshan Liu Dapeng Wang Deqin Yan Yu Sang |
| author_facet | Deshan Liu Dapeng Wang Deqin Yan Yu Sang |
| author_sort | Deshan Liu |
| collection | DOAJ |
| description | The key problem for attribute reduction to information systems is how to evaluate the importance of an attribute. The algorithms are challenged by the variety of data forms in information system. Based on rough sets theory we present a new approach to attribute reduction for incomplete information systems and fuzzy valued information systems. In order to evaluate the importance of an attribute effectively, a novel algorithm with rigorous theorem is proposed. Experiments show the effect of proposed algorithm. |
| format | Article |
| id | doaj-art-2f65989ee7b1460799984650132bd914 |
| institution | Kabale University |
| issn | 1085-3375 1687-0409 |
| language | English |
| publishDate | 2014-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Abstract and Applied Analysis |
| spelling | doaj-art-2f65989ee7b1460799984650132bd9142025-02-03T01:20:28ZengWileyAbstract and Applied Analysis1085-33751687-04092014-01-01201410.1155/2014/382967382967Approximate Accuracy Approaches to Attribute Reduction for Information SystemsDeshan Liu0Dapeng Wang1Deqin Yan2Yu Sang3College of Computer and Information Technology, Liaoning Normal University, Dalian 116029, ChinaCollege of Computer and Information Technology, Liaoning Normal University, Dalian 116029, ChinaCollege of Computer and Information Technology, Liaoning Normal University, Dalian 116029, ChinaInstitute of Computing Technology, Research Institute of Exploration and Development, Liaohe Oilfield, PetroChina, No. 98 Oil Street, Panjin 124010, ChinaThe key problem for attribute reduction to information systems is how to evaluate the importance of an attribute. The algorithms are challenged by the variety of data forms in information system. Based on rough sets theory we present a new approach to attribute reduction for incomplete information systems and fuzzy valued information systems. In order to evaluate the importance of an attribute effectively, a novel algorithm with rigorous theorem is proposed. Experiments show the effect of proposed algorithm.http://dx.doi.org/10.1155/2014/382967 |
| spellingShingle | Deshan Liu Dapeng Wang Deqin Yan Yu Sang Approximate Accuracy Approaches to Attribute Reduction for Information Systems Abstract and Applied Analysis |
| title | Approximate Accuracy Approaches to Attribute Reduction for Information Systems |
| title_full | Approximate Accuracy Approaches to Attribute Reduction for Information Systems |
| title_fullStr | Approximate Accuracy Approaches to Attribute Reduction for Information Systems |
| title_full_unstemmed | Approximate Accuracy Approaches to Attribute Reduction for Information Systems |
| title_short | Approximate Accuracy Approaches to Attribute Reduction for Information Systems |
| title_sort | approximate accuracy approaches to attribute reduction for information systems |
| url | http://dx.doi.org/10.1155/2014/382967 |
| work_keys_str_mv | AT deshanliu approximateaccuracyapproachestoattributereductionforinformationsystems AT dapengwang approximateaccuracyapproachestoattributereductionforinformationsystems AT deqinyan approximateaccuracyapproachestoattributereductionforinformationsystems AT yusang approximateaccuracyapproachestoattributereductionforinformationsystems |