C4.5: programs for machine learning
C4.5: programs for machine learning
Fast training of support vector machines using sequential minimal optimization
Advances in kernel methods
Data mining: practical machine learning tools and techniques with Java implementations
Data mining: practical machine learning tools and techniques with Java implementations
Using Model Trees for Classification
Machine Learning
Knowledge Discovery and Measures of Interest
Knowledge Discovery and Measures of Interest
Generating Accurate Rule Sets Without Global Optimization
ICML '98 Proceedings of the Fifteenth International Conference on Machine Learning
CCAIIA: Clustering Categorial Attributed into Interseting Accociation Rules
PAKDD '98 Proceedings of the Second Pacific-Asia Conference on Research and Development in Knowledge Discovery and Data Mining
An Analysis of Quantitative Measures Associated with Rules
PAKDD '99 Proceedings of the Third Pacific-Asia Conference on Methodologies for Knowledge Discovery and Data Mining
Selecting the right interestingness measure for association patterns
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Peculiarity Oriented Multidatabase Mining
IEEE Transactions on Knowledge and Data Engineering
Evaluation of rule interestingness measures with a clinical dataset on hepatitis
PKDD '04 Proceedings of the 8th European Conference on Principles and Practice of Knowledge Discovery in Databases
Evaluation of rule interestingness measures in medical knowledge discovery in databases
Artificial Intelligence in Medicine
Finding Functional Groups of Objective Rule Evaluation Indices Using PCA
PAKM '08 Proceedings of the 7th International Conference on Practical Aspects of Knowledge Management
Investigating Accuracies of Classifications for Randomized Imbalanced Class Distributions
Fundamenta Informaticae - Cognitive Informatics, Cognitive Computing, and Their Denotational Mathematical Foundations (II)
A Comparison of Composed Objective Rule Evaluation Indices Using PCA and Single Indices
RSKT '09 Proceedings of the 4th International Conference on Rough Sets and Knowledge Technology
Improving a rule evaluation support method based on objective indices
International Journal of Advanced Intelligence Paradigms
Research on sustainable development based on neural network
CCDC'09 Proceedings of the 21st annual international conference on Chinese control and decision conference
Evaluation model of learning effect based on adaptive wavelet neural network
ICNC'09 Proceedings of the 5th international conference on Natural computation
Investigating Accuracies of Classifications for Randomized Imbalanced Class Distributions
Fundamenta Informaticae - Cognitive Informatics, Cognitive Computing, and Their Denotational Mathematical Foundations (II)
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In this paper, we present a novel rule evaluation support method for post-processing of mined results with rule evaluation models based on objective indexes. Post-processing of mined results is one of the key issues to make a data mining process successfully. However, it is difficult for human experts to evaluate many thousands of rules from a large dataset with noises completely. To reduce the costs of rule evaluation procedures, we have developed the rule evaluation support method with rule evaluation models, which are obtained with objective rule evaluation indexes and evaluations of a human expert for each rule. Since the method is needed more accurate rule evaluation models, we have compared learning algorithms to construct rule evaluation models with the actual meningitis data mining result and actual rule sets from UCI datasets. Then we show the availability of our adaptive rule evaluation support method.