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IJCNN-91-Seattle: International Joint Conference on Neural Networks (Cat. No.91CH3049-4)

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Projection pursuit learning

Content Provider	IEEE Xplore Digital Library
Author	Zhao, Y. Atkeson, C.G.
Copyright Year	1991
Description	Author affiliation: Artificial Intelligence Lab., MIT, Cambridge, MA, USA (Zhao, Y.; Atkeson, C.G.)
Abstract	A learning model based on a nonparametric statistical technique, projection pursuit regression, is studied. Projection pursuit is a nonparametric statistical technique to find interesting low-dimensional projections of high-dimensional data sets. Projection pursuit regression approximates a function of q variables by a sum of nonlinear functions of linear combinations of the q variables, which is related to current neural network models. A training algorithm for projection pursuit learning, called backfitting, is investigated. An example of the application of this model is demonstrated.
Starting Page	869
Ending Page	874
File Size	256762
Page Count	6
File Format	PDF
ISBN	0780301641
DOI	10.1109/IJCNN.1991.155293
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1991-07-08
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Neural networks Function approximation Algorithm design and analysis Feedforward neural networks Learning Pursuit algorithms Backpropagation algorithms Artificial intelligence Laboratories Terminology
Content Type	Text
Resource Type	Article

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