Soft set approach for decision attribute selection in data clustering
Clustering is one of the fundamental operations in data mining that cluster set of heterogeneous data objects into smaller homogeneous classes. Using clustering attribute (decision attribute) is one of the data clustering techniques. Soft set theory is a new mathematical tool applying in clustering...
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| Format: | Undergraduates Project Papers |
| Language: | English |
| Published: |
2013
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| Online Access: | http://umpir.ump.edu.my/id/eprint/8719/1/CD8312%20%40%2073.pdf |
| _version_ | 1796990490863730688 |
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| author | Lok, Leh Leong |
| author_facet | Lok, Leh Leong |
| author_sort | Lok, Leh Leong |
| collection | UMP |
| description | Clustering is one of the fundamental operations in data mining that cluster set of heterogeneous data objects into smaller homogeneous classes. Using clustering attribute (decision attribute) is one of the data clustering techniques. Soft set theory is a new mathematical tool applying in clustering applications in databases circumstances. Hence,the research aim is to find the practical technique of soft set theory for decision attribute selection in soft set theory. The test is been done by using two UCI benchmark datasets to determine the speed of execution time for soft set approach with rough set techniques, that are Total Roughness (TR), Min-Min Roughness (MMR) and Maximum Dependency of Attributes (MDA). The results show that the proposed technique provides faster decision for selecting a clustering attribute |
| first_indexed | 2024-03-06T11:52:21Z |
| format | Undergraduates Project Papers |
| id | UMPir8719 |
| institution | Universiti Malaysia Pahang |
| language | English |
| last_indexed | 2024-03-06T11:52:21Z |
| publishDate | 2013 |
| record_format | dspace |
| spelling | UMPir87192021-06-30T03:42:48Z http://umpir.ump.edu.my/id/eprint/8719/ Soft set approach for decision attribute selection in data clustering Lok, Leh Leong QA76 Computer software Clustering is one of the fundamental operations in data mining that cluster set of heterogeneous data objects into smaller homogeneous classes. Using clustering attribute (decision attribute) is one of the data clustering techniques. Soft set theory is a new mathematical tool applying in clustering applications in databases circumstances. Hence,the research aim is to find the practical technique of soft set theory for decision attribute selection in soft set theory. The test is been done by using two UCI benchmark datasets to determine the speed of execution time for soft set approach with rough set techniques, that are Total Roughness (TR), Min-Min Roughness (MMR) and Maximum Dependency of Attributes (MDA). The results show that the proposed technique provides faster decision for selecting a clustering attribute 2013 Undergraduates Project Papers NonPeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/8719/1/CD8312%20%40%2073.pdf Lok, Leh Leong (2013) Soft set approach for decision attribute selection in data clustering. Faculty of Computer System And Software Engineering, Universiti Malaysia Pahang. |
| spellingShingle | QA76 Computer software Lok, Leh Leong Soft set approach for decision attribute selection in data clustering |
| title | Soft set approach for decision attribute selection in data clustering |
| title_full | Soft set approach for decision attribute selection in data clustering |
| title_fullStr | Soft set approach for decision attribute selection in data clustering |
| title_full_unstemmed | Soft set approach for decision attribute selection in data clustering |
| title_short | Soft set approach for decision attribute selection in data clustering |
| title_sort | soft set approach for decision attribute selection in data clustering |
| topic | QA76 Computer software |
| url | http://umpir.ump.edu.my/id/eprint/8719/1/CD8312%20%40%2073.pdf |
| work_keys_str_mv | AT loklehleong softsetapproachfordecisionattributeselectionindataclustering |