Efficient Distributed Genetic Algorithm for Rule Extraction

Authors:
Antonio Peregrin;Miguel Angel Rodriguez
Affiliations:
-;-
Venue:
HIS '08 Proceedings of the 2008 8th International Conference on Hybrid Intelligent Systems
Year:
2008

Citing 0
Cited 2

An Evolutionary Ensemble-Based Method for Rule Extraction with Distributed Data

HAIS '09 Proceedings of the 4th International Conference on Hybrid Artificial Intelligence Systems
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Abstract

This paper presents an efficient distributed genetic algorithm for classification rules extraction in datamining, which is based on a new method of dynamic data distribution applied to parallelism using networks of computers in order to mine large datasets. The presented algorithm shows many advantages when compared with other distributed algorithms proposed in the specific literature. In this way, some results are presented showing significant learning rate speed-up without compromising other features.