Instance-Based Learning Algorithms
Machine Learning
A hybrid nearest-neighbor and nearest-hyperrectangle algorithm
ECML-94 Proceedings of the European conference on machine learning on Machine Learning
Reduction Techniques for Instance-BasedLearning Algorithms
Machine Learning
A case-based approach using inductive indexing for corporate bond rating
Decision Support Systems - Decision-making and E-commerce systems
Advances in Instance Selection for Instance-Based Learning Algorithms
Data Mining and Knowledge Discovery
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
Estimating Software Development Effort with Case-Based Reasoning
ICCBR '97 Proceedings of the Second International Conference on Case-Based Reasoning Research and Development
A new hybrid case-based architecture for medical diagnosis
Information Sciences—Informatics and Computer Science: An International Journal
Adapting the CBA algorithm by means of intensity of implication
Information Sciences—Informatics and Computer Science: An International Journal - Special issue: Dealing with uncertainty in data mining and information extraction
Mining spatial association rules in image databases
Information Sciences: an International Journal
A new approach to classification based on association rule mining
Decision Support Systems
MCAR: multi-class classification based on association rule
AICCSA '05 Proceedings of the ACS/IEEE 2005 International Conference on Computer Systems and Applications
Finding Prototypes For Nearest Neighbor Classifiers
IEEE Transactions on Computers
Mining competent case bases for case-based reasoning
Artificial Intelligence
Remembering to forget: a competence-preserving case deletion policy for case-based reasoning systems
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
Looking into the seeds of time: Discovering temporal patterns in large transaction sets
Information Sciences: an International Journal
A parallel algorithm for mining multiple partial periodic patterns
Information Sciences: an International Journal
Flexible online association rule mining based on multidimensional pattern relations
Information Sciences: an International Journal
A false negative approach to mining frequent itemsets from high speed transactional data streams
Information Sciences: an International Journal
The condensed nearest neighbor rule (Corresp.)
IEEE Transactions on Information Theory
The reduced nearest neighbor rule (Corresp.)
IEEE Transactions on Information Theory
An algorithm for a selective nearest neighbor decision rule (Corresp.)
IEEE Transactions on Information Theory
Gaussian case-based reasoning for business failure prediction with empirical data in China
Information Sciences: an International Journal
Recognizing yield patterns through hybrid applications of machine learning techniques
Information Sciences: an International Journal
Loss and gain functions for CBR retrieval
Information Sciences: an International Journal
Nearest neighbor editing aided by unlabeled data
Information Sciences: an International Journal
A Hybrid Solution for Advice in the Knowledge Management Field
HAIS '09 Proceedings of the 4th International Conference on Hybrid Artificial Intelligence Systems
Hybrid model for learner modelling and feedback prioritisation in exploratory learning
International Journal of Hybrid Intelligent Systems - CIMA-08
Principal component case-based reasoning ensemble for business failure prediction
Information and Management
A new similarity measure in formal concept analysis for case-based reasoning
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
ICMB'10 Proceedings of the Second international conference on Medical Biometrics
Expert Systems with Applications: An International Journal
| Hi-index | 0.08 |
Case-based reasoning (CBR) is a type of problem solving technique which uses previous cases to solve new, unseen and different problems. Although a larger number of cases in the memory can improve the coverage of the problem space, the retrieval efficiency will be downgraded if the size of the case-base grows to an unacceptable level. In CBR systems, the tradeoff between the number of cases stored in the case-base and the retrieval efficiency is a critical issue. This paper addresses the problem of case-base maintenance by developing a new technique, the association-based case reduction technique (ACRT), to reduce the size of the case-base in order to enhance the efficiency while maintaining or even improving the accuracy of the CBR. The experiments on 12 UCI datasets and an actual case from Taiwan's hospital have shown superior generalization accuracy for CBR with ACRT (CBR-ACRT) as well as a greater solving efficiency.