C4.5: programs for machine learning
C4.5: programs for machine learning
Genetic algorithms + data structures = evolution programs (3rd ed.)
Genetic algorithms + data structures = evolution programs (3rd ed.)
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
Applications of Learning Classifier Systems
Applications of Learning Classifier Systems
JADE-Based A-Team as a Tool for Implementing Population-Based Algorithms
ISDA '06 Proceedings of the Sixth International Conference on Intelligent Systems Design and Applications - Volume 03
Selecting representative examples and attributes by a genetic algorithm
Intelligent Data Analysis
Classifier fitness based on accuracy
Evolutionary Computation
Learning Classifier Systems in Data Mining
Learning Classifier Systems in Data Mining
Data Reduction Algorithm for Machine Learning and Data Mining
IEA/AIE '08 Proceedings of the 21st international conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems: New Frontiers in Applied Artificial Intelligence
Adaptive integrated image segmentation and object recognition
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
A-Teams and Their Applications
ICCCI '09 Proceedings of the 1st International Conference on Computational Collective Intelligence. Semantic Web, Social Networks and Multiagent Systems
Distributed learning with data reduction
Transactions on computational collective intelligence IV
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This paper focuses on classification tasks. The goal of the paper is to propose a framework for adaptive and integrated machine classification and to investigate the effect of different adaptation and integration schemes. After having introduced several integration and adaptation schemes a framework for adaptive and integrated classification in the form of the software shell is proposed. The shell allows for integrating data pre-processing with data mining stages using population-based and A-Team techniques. The approach was validated experimentally. Experiment results have shown that integrated and adaptive classification outperforms traditional approaches.