Efficient Rule Generation for Associative Classification
Associative classification (AC) is a mining technique that integrates classification and association rule mining to perform classification on unseen data instances. AC is one of the effective classification techniques that applies the generated rules to perform classification. In particular, the num...
Main Authors: | Chartwut Thanajiranthorn, Panida Songram |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2020-11-01
|
Series: | Algorithms |
Subjects: | |
Online Access: | https://www.mdpi.com/1999-4893/13/11/299 |
Similar Items
-
C-MWCAR: Classification Based on Multiple Weighted Class Association Rules
by: Gui Li, et al.
Published: (2023-07-01) -
ACMKC: A Compact Associative Classification Model Using K-Modes Clustering with Rule Representations by Coverage
by: Jamolbek Mattiev, et al.
Published: (2023-09-01) -
Coverage-Based Classification Using Association Rule Mining
by: Jamolbek Mattiev, et al.
Published: (2020-10-01) -
The Effect of “Directness” of the Distance Metric to Produce Compact and Accurate Associative Classification Models
by: Jamolbek Mattiev, et al.
Published: (2022-09-01) -
Proposed Parallel Association Rules Algorithm
by: Emad kadhiem Jabbar, et al.
Published: (2014-01-01)