A new approach to classification based on association rule mining

Authors:
Guoqing Chen;Hongyan Liu;Lan Yu;Qiang Wei;Xing Zhang
Affiliations:
Department of Management Science and Engineering, School of Economics and Management, Tsinghua University, Beijing, China;Department of Management Science and Engineering, School of Economics and Management, Tsinghua University, Beijing, China;Department of Management Science and Engineering, School of Economics and Management, Tsinghua University, Beijing, China;Department of Management Science and Engineering, School of Economics and Management, Tsinghua University, Beijing, China;Department of Management Science and Engineering, School of Economics and Management, Tsinghua University, Beijing, China
Venue:
Decision Support Systems
Year:
2006

Citing 19
Cited 24

Computer systems that learn: classification and prediction methods from statistics, neural nets, machine learning, and expert systems

Computer systems that learn: classification and prediction methods from statistics, neural nets, machine learning, and expert systems
C4.5: programs for machine learning

C4.5: programs for machine learning
Mining association rules between sets of items in large databases

SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
Fast sequential and parallel algorithms for association rule mining: a comparison

Fast sequential and parallel algorithms for association rule mining: a comparison
Data mining using two-dimensional optimized association rules: scheme, algorithms, and visualization

SIGMOD '96 Proceedings of the 1996 ACM SIGMOD international conference on Management of data
Dynamic itemset counting and implication rules for market basket data

SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
From data mining to knowledge discovery: an overview

Advances in knowledge discovery and data mining
Bayesian Network Classifiers

Machine Learning - Special issue on learning with probabilistic representations
Extending naïve Bayes classifiers using long itemsets

KDD '99 Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining
Data mining: practical machine learning tools and techniques with Java implementations

Data mining: practical machine learning tools and techniques with Java implementations
Simple association rules (SAR) and the SAR-based rule discovery

Computers and Industrial Engineering
Fuzzy association rules and the extended mining algorithms

Information Sciences—Informatics and Computer Science: An International Journal
Database Mining: A Performance Perspective

IEEE Transactions on Knowledge and Data Engineering
SLIQ: A Fast Scalable Classifier for Data Mining

EDBT '96 Proceedings of the 5th International Conference on Extending Database Technology: Advances in Database Technology
CMAR: Accurate and Efficient Classification Based on Multiple Class-Association Rules

ICDM '01 Proceedings of the 2001 IEEE International Conference on Data Mining
Decision Tables: Scalable Classification Exploring RDBMS Capabilities

VLDB '00 Proceedings of the 26th International Conference on Very Large Data Bases
Fast Algorithms for Mining Association Rules in Large Databases

VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
SPRINT: A Scalable Parallel Classifier for Data Mining

VLDB '96 Proceedings of the 22th International Conference on Very Large Data Bases
Constraint-Based Rule Mining in Large, Dense Databases

ICDE '99 Proceedings of the 15th International Conference on Data Engineering

Compact fuzzy association rule-based classifier

Expert Systems with Applications: An International Journal
An association-based case reduction technique for case-based reasoning

Information Sciences: an International Journal
Entropy-based associative classification algorithm for mining manufacturing data

International Journal of Computer Integrated Manufacturing
CSMC: A combination strategy for multi-class classification based on multiple association rules

Knowledge-Based Systems
Rule Extraction from Neural Networks Via Ant Colony Algorithm for Data Mining Applications

Learning and Intelligent Optimization
TACO-miner: An ant colony based algorithm for rule extraction from trained neural networks

Expert Systems with Applications: An International Journal
Discovery of unapparent association rules based on extracted probability

Decision Support Systems
A soft computing-based approach for integrated training and rule extraction from artificial neural networks: DIFACONN-miner

Applied Soft Computing
Integrating classification capability and reliability in associative classification: A β-stronger model

Expert Systems with Applications: An International Journal
Mining associative classification rules with stock trading data - A GA-based method

Knowledge-Based Systems
A modified pittsburg approach to design a genetic fuzzy rule-based classifier from data

ICAISC'10 Proceedings of the 10th international conference on Artificial intelligence and soft computing: Part I
Building a highly-compact and accurate associative classifier

Applied Intelligence
Interpreting the web-mining results by cognitive map and association rule approach

Information Processing and Management: an International Journal
Classification based on association rules: A lattice-based approach

Expert Systems with Applications: An International Journal
Selecting feature subset via constraint association rules

PAKDD'12 Proceedings of the 16th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining - Volume Part II
Gravitation based classification

Information Sciences: an International Journal
Analysis of association rule mining on quantitative concept lattice

AICI'12 Proceedings of the 4th international conference on Artificial Intelligence and Computational Intelligence
The bank loan approval decision from multiple perspectives

Expert Systems with Applications: An International Journal
A New Approach to Associative Classification Based on Binary Multi-objective Particle Swarm Optimization

International Journal of Applied Metaheuristic Computing
Correlating medical-dependent query features with image retrieval models using association rules

Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
Real-time rule-based classification of player types in computer games

User Modeling and User-Adapted Interaction
From clicking to consideration: A business intelligence approach to estimating consumers' consideration probabilities

Decision Support Systems
CBC: An associative classifier with a small number of rules

Decision Support Systems
A novel feature subset selection algorithm based on association rule mining

Intelligent Data Analysis

Quantified Score

Hi-index	0.01

Visualization

Abstract

Classification is one of the key issues in the fields of decision sciences and knowledge discovery. This paper presents a new approach for constructing a classifier, based on an extended association rule mining technique in the context of classification. The characteristic of this approach is threefold: first, applying the information gain measure to the generation of candidate itemsets; second, integrating the process of frequent itemsets generation with the process of rule generation; third, incorporating strategies for avoiding rule redundancy and conflicts into the mining process. The corresponding mining algorithm proposed, namely GARC (Gain based Association Rule Classification), produces a classifier with satisfactory classification accuracy, compared with other classifiers (e.g., C4.5, CBA, SVM, NN). Moreover, in terms of association rule based classification, GARC could filter out many candidate itemsets in the generation process, resulting in a much smaller set of rules than that of CBA.