C4.5: programs for machine learning
C4.5: programs for machine learning
Data mining: practical machine learning tools and techniques with Java implementations
Data mining: practical machine learning tools and techniques with Java implementations
Conflict handling in collaborative search
Conflicting agents
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Evolving data into mining solutions for insights
Communications of the ACM - Evolving data mining into solutions for insights
Toward Multidatabase Mining: Identifying Relevant Databases
IEEE Transactions on Knowledge and Data Engineering
Generating Accurate Rule Sets Without Global Optimization
ICML '98 Proceedings of the Fifteenth International Conference on Machine Learning
Cooperation of heterogeneous provers
IJCAI'99 Proceedings of the 16th international joint conference on Artifical intelligence - Volume 1
CoLe: A Cooperative Data Mining Approach and Its Application to Early Diabetes Detection
ICDM '05 Proceedings of the Fifth IEEE International Conference on Data Mining
Improving the efficiency of distributed data mining using an adjustment work flow
MLDM'13 Proceedings of the 9th international conference on Machine Learning and Data Mining in Pattern Recognition
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We present CoLe, a model for cooperative agents for mining knowledge from heterogeneous data. CoLe allows for the cooperation of different mining agents and the combination of the mined knowledge into knowledge structures that no individual mining agent can produce alone. CoLe organizes the work in rounds so that knowledge discovered by one mining agent can help others in the next round. We implemented a multi-agent system based on CoLe for mining diabetes data, including an agent using a genetic algorithm for mining event sequences, an agent with improvements to the PART algorithm for our problem and a combination agent with methods to produce hybrid rules containing conjunctive and sequence conditions. In our experiments, the CoLe-based system outperformed the individual mining algorithms, with better rules and more rules of a certain quality. From the medical perspective, our system confirmed hypertension has a tight relation to diabetes, and it also suggested connections new to medical doctors.