Communication Efficient Construction of Decision Trees Over Heterogeneously Distributed Data
ICDM '04 Proceedings of the Fourth IEEE International Conference on Data Mining
Agent based distributed data mining
PDCAT'04 Proceedings of the 5th international conference on Parallel and Distributed Computing: applications and Technologies
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This paper describes the implementation of a distributed data mining system. The system consists of a web server, a pre-processor for data preparation, a mediator, and agents. A distributed learning algorithm of a decision tree in an agent-mediator communication mechanism is the most important and difficult to achieve the distributed data mining in this system, in the view of implementation. The algorithm has successfully been implemented with several techniques. Its implementation is presented in a UML (Unified Modeling Language) sequence diagram.