Cellular Automata Based Pattern Classifying Machine for Distributed Data Mining
In this paper, we present the design and application of a pattern classifying machine (PCM) for distributed data mining (DDM) environment. The PCM is based on a special class of sparse network referred to as Cellular Automata (CA). The desired CA are evolved with an efficient formulation of Genetic Algorithm (GA). Extensive experimental results with respect to classification accuracy and memory overhead confirm the scalability of the PCM to handle distributed datasets.
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