Artificial intelligence (3rd ed.)
Artificial intelligence (3rd ed.)
C4.5: programs for machine learning
C4.5: programs for machine learning
Variable precision rough set model
Journal of Computer and System Sciences
Discovery through rough set theory
Communications of the ACM
Data mining: practical machine learning tools and techniques with Java implementations
Data mining: practical machine learning tools and techniques with Java implementations
Data mining: concepts and techniques
Data mining: concepts and techniques
Automatic Construction of Decision Trees from Data: A Multi-Disciplinary Survey
Data Mining and Knowledge Discovery
Benchmarking Attribute Selection Techniques for Discrete Class Data Mining
IEEE Transactions on Knowledge and Data Engineering
Data gravitation based classification
Information Sciences: an International Journal
A DGC-based data classification method used for abnormal network intrusion detection
ICONIP'06 Proceedings of the 13th international conference on Neural information processing - Volume Part III
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The proposed hybridized framework is composed of traditional Rough Set (RS) approach and classical Decision Tree (DT) induction algorithm. RS helps to identify dominant attributes and DT algorithm results in simpler, and generalized classifier. Experimental results obtained by applying the hybridized rough set framework and related base algorithms on data sets from three categories are presented in this paper. Accuracy, complexity, number of rules and number of attributes assess the performance of candidate algorithms. The results indicate that the proposed framework is effective, as a model for classification