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This paper presents the design of a hybrid learning model, termed as neural network tree (NNTree). It incorporates the advantages of both decision tree and neural network. An NNTree is a decision tree, where each non-terminal node contains a neural network. The idea of the proposed method is to use the framework of multilayer perceptron to design tree-structured pattern classifier. At each non-terminal...
Unlike to traditional hierarchical and partitional clustering algorithms which always fail to deal with very large databases, a neural network architecture, projective adaptive resonance theory (PART), is developed for the high dimensional space clustering. However, the success of the PART algorithm depends on both accurate parameters and satisfied orders of input data sets. These disadvantages prevent...
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