Rule induction with CN2: some recent improvements
EWSL-91 Proceedings of the European working session on learning on Machine learning
C4.5: programs for machine learning
C4.5: programs for machine learning
Dynamic itemset counting and implication rules for market basket data
SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
Mining frequent patterns without candidate generation
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
Multipass algorithms for mining association rules in text databases
Knowledge and Information Systems
Beyond Market Baskets: Generalizing Association Rules to Dependence Rules
Data Mining and Knowledge Discovery
ECML '93 Proceedings of the European Conference on Machine Learning
CMAR: Accurate and Efficient Classification Based on Multiple Class-Association Rules
ICDM '01 Proceedings of the 2001 IEEE International Conference on Data Mining
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
Rule Evaluation Measures: A Unifying View
ILP '99 Proceedings of the 9th International Workshop on Inductive Logic Programming
ART: A Hybrid Classification Model
Machine Learning
An Evaluation of Approaches to Classification Rule Selection
ICDM '04 Proceedings of the Fourth IEEE International Conference on Data Mining
Mining top-K covering rule groups for gene expression data
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
A New Association Rule-Based Text Classifier Algorithm
ICTAI '05 Proceedings of the 17th IEEE International Conference on Tools with Artificial Intelligence
Multiple labels associative classification
Knowledge and Information Systems
CoMMA: a framework for integrated multimedia mining using multi-relational associations
Knowledge and Information Systems
On Mining Instance-Centric Classification Rules
IEEE Transactions on Knowledge and Data Engineering
MCAR: multi-class classification based on association rule
AICCSA '05 Proceedings of the ACS/IEEE 2005 International Conference on Computer Systems and Applications
Generalizing the notion of confidence
Knowledge and Information Systems
A Novel Rule Weighting Approach in Classification Association Rule Mining
ICDMW '07 Proceedings of the Seventh IEEE International Conference on Data Mining Workshops
Boosting text segmentation via progressive classification
Knowledge and Information Systems
A Novel Rule Ordering Approach in Classification Association Rule Mining
MLDM '07 Proceedings of the 5th international conference on Machine Learning and Data Mining in Pattern Recognition
Direct Discriminative Pattern Mining for Effective Classification
ICDE '08 Proceedings of the 2008 IEEE 24th International Conference on Data Engineering
ICDM '09 Proceedings of the 9th Industrial Conference on Advances in Data Mining. Applications and Theoretical Aspects
Algorithms for mining frequent itemsets in static and dynamic datasets
Intelligent Data Analysis
Practical application of associative classifier for document classification
AIRS'05 Proceedings of the Second Asia conference on Asia Information Retrieval Technology
Threshold tuning for improved classification association rule mining
PAKDD'05 Proceedings of the 9th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining
| Hi-index | 0.00 |
In this paper, an accurate classifier based on Class Association Rules CARs, called CAR-NF, is proposed. CAR-NF introduces a new strategy for computing CARs, using the Netconf as measure of interest, that allows to prune the CAR search space for building specific rules with high Netconf. Moreover, we propose and prove a proposition that supports the use of a Netconf threshold value equal to 0.5 for mining the CARs. Additionally, a new way for ordering the set of CARs based on their rule sizes and Netconf values is introduced in CAR-NF. The ordering strategy together with the "Best K rules" satisfaction mechanism allows CAR-NF to have better accuracy than CBA, CMAR, CPAR, TFPC and HARMONY classifiers, the best classifiers based on CARs reported in the literature.