Implementing projection pursuit learning |
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Authors: | Ying Zhao Atkeson CG |
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Affiliation: | Artificial Intelligence Lab., MIT, Cambridge, MA. |
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Abstract: | This paper examines the implementation of projection pursuit regression (PPR) in the context of machine learning and neural networks. We propose a parametric PPR with direct training which achieves improved training speed and accuracy when compared with nonparametric PPR. Analysis and simulations are done for heuristics to choose good initial projection directions. A comparison of a projection pursuit learning network with a single hidden-layer sigmoidal neural network shows why grouping hidden units in a projection pursuit learning network is useful. Learning robot arm inverse dynamics is used as an example problem. |
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