Rough decision rules extraction and reduction based on granular computing
Rule mining was an important research content of data mining,and it was also a hot research topic in the fields of decision support system,artificial intelligence,recommendation system,etc,where attribute reduction and minimal rule set extraction were the key links.Most importantly,the efficiency of...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | zho |
| Published: |
Editorial Department of Journal on Communications
2016-10-01
|
| Series: | Tongxin xuebao |
| Subjects: | |
| Online Access: | http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2016244/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1841539482429423616 |
|---|---|
| author | Hong-can YAN Feng ZHANG Bao-xiang LIU |
| author_facet | Hong-can YAN Feng ZHANG Bao-xiang LIU |
| author_sort | Hong-can YAN |
| collection | DOAJ |
| description | Rule mining was an important research content of data mining,and it was also a hot research topic in the fields of decision support system,artificial intelligence,recommendation system,etc,where attribute reduction and minimal rule set extraction were the key links.Most importantly,the efficiency of extraction was determined by its application.The rough set model and granular computing theory were applied to the decision rule reduction.The decision table was granulated by granulation function,the grain of membership and the concept granular set construction algorithm gener-ated the initial concept granular set.Therefore,attribute reduction could be realized by the distinguish operator of concept granule,and decision rules extraction could be achieved by visualization of concept granule lattice.Experimental result shows that the method is easier to be applied to computer programming and it is more efficient and practical than the existing methods. |
| format | Article |
| id | doaj-art-1cfe48c13c5b4f48bf5868a3685e69aa |
| institution | Kabale University |
| issn | 1000-436X |
| language | zho |
| publishDate | 2016-10-01 |
| publisher | Editorial Department of Journal on Communications |
| record_format | Article |
| series | Tongxin xuebao |
| spelling | doaj-art-1cfe48c13c5b4f48bf5868a3685e69aa2025-01-14T07:11:05ZzhoEditorial Department of Journal on CommunicationsTongxin xuebao1000-436X2016-10-0137303559705660Rough decision rules extraction and reduction based on granular computingHong-can YANFeng ZHANGBao-xiang LIURule mining was an important research content of data mining,and it was also a hot research topic in the fields of decision support system,artificial intelligence,recommendation system,etc,where attribute reduction and minimal rule set extraction were the key links.Most importantly,the efficiency of extraction was determined by its application.The rough set model and granular computing theory were applied to the decision rule reduction.The decision table was granulated by granulation function,the grain of membership and the concept granular set construction algorithm gener-ated the initial concept granular set.Therefore,attribute reduction could be realized by the distinguish operator of concept granule,and decision rules extraction could be achieved by visualization of concept granule lattice.Experimental result shows that the method is easier to be applied to computer programming and it is more efficient and practical than the existing methods.http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2016244/granular computingmembership function of graindistinguish operatorconcept granule latticerules ex-traction |
| spellingShingle | Hong-can YAN Feng ZHANG Bao-xiang LIU Rough decision rules extraction and reduction based on granular computing Tongxin xuebao granular computing membership function of grain distinguish operator concept granule lattice rules ex-traction |
| title | Rough decision rules extraction and reduction based on granular computing |
| title_full | Rough decision rules extraction and reduction based on granular computing |
| title_fullStr | Rough decision rules extraction and reduction based on granular computing |
| title_full_unstemmed | Rough decision rules extraction and reduction based on granular computing |
| title_short | Rough decision rules extraction and reduction based on granular computing |
| title_sort | rough decision rules extraction and reduction based on granular computing |
| topic | granular computing membership function of grain distinguish operator concept granule lattice rules ex-traction |
| url | http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2016244/ |
| work_keys_str_mv | AT hongcanyan roughdecisionrulesextractionandreductionbasedongranularcomputing AT fengzhang roughdecisionrulesextractionandreductionbasedongranularcomputing AT baoxiangliu roughdecisionrulesextractionandreductionbasedongranularcomputing |