Algorithm Study of New Association Rules and Classification Rules in Data Mining. Issue 1 (January 2021)
- Record Type:
- Journal Article
- Title:
- Algorithm Study of New Association Rules and Classification Rules in Data Mining. Issue 1 (January 2021)
- Main Title:
- Algorithm Study of New Association Rules and Classification Rules in Data Mining
- Authors:
- Yang, Xiaobo
- Abstract:
- Abstract: In order to further improve the efficiency of data mining, it proposes a kind of data mining algorithm based on new association rules and classification rules. Specific research process is as follows. Firstly, MDML-PP algorithm is analyzed and applied to the multi-dimensional multi-level association rules in data mining, and then selects the test data sets for performance evaluation, meanwhile, it also studies the multi-support rate cut and classification rule mining algorithm, which is applied to multi-support rate classification rules in data mining, finally, using the compare experiment to verify the effectiveness of multi-support rate classification rules. The results show that the proposed algorithm in this paper can be better used in data mining with multi-dimensional and multi-layer association rules, which can improve the efficiency and quality of data mining.
- Is Part Of:
- Journal of physics. Volume 1732:Issue 1(2021)
- Journal:
- Journal of physics
- Issue:
- Volume 1732:Issue 1(2021)
- Issue Display:
- Volume 1732, Issue 1 (2021)
- Year:
- 2021
- Volume:
- 1732
- Issue:
- 1
- Issue Sort Value:
- 2021-1732-0001-0000
- Page Start:
- Page End:
- Publication Date:
- 2021-01
- Subjects:
- Physics -- Congresses
530.5 - Journal URLs:
- http://www.iop.org/EJ/journal/1742-6596 ↗
http://ioppublishing.org/ ↗ - DOI:
- 10.1088/1742-6596/1732/1/012070 ↗
- Languages:
- English
- ISSNs:
- 1742-6588
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 5036.223000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 25481.xml