Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/116801
Title: Using nearest neighbor learning to improve Sanger's tree-structured algorithm
Authors: Chen, Chung-Chih 
Issue Date: 1992
Citation: Chen, Chung-Chih (1992). Using nearest neighbor learning to improve Sanger's tree-structured algorithm. 1991 IEEE International Joint Conference on Neural Networks : 827-832. ScholarBank@NUS Repository.
Abstract: The author identifies several different neural network models which are related to nearest neighbor learning. They include radial basis functions, sparse distributed memory, and localized receptive fields. One way to improve the neural networks' performance is by using the cooperation of different learning algorithms. The prediction of chaotic time series is used as an example to show how nearest neighbor learning can be employed to improve Sanger's tree-structured algorithm which predicts future values of the Mackey-Glass differential delay equation.
Source Title: 1991 IEEE International Joint Conference on Neural Networks
URI: http://scholarbank.nus.edu.sg/handle/10635/116801
ISBN: 0780302273
Appears in Collections:Staff Publications

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