Neural networks and statistics. (response to Hugh Gauch, American Scientist, vol. 81, Sep-Oct, 1993)

Statistical noise data analysis methods include neural-network techniques that are useful statistical tools for historical-data-based judgment. Neural-network statistical properties include noise-tolerance, data overfitting minimization and proper model accuracy-size balance. Neural-networks are yet...

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Bibliographic Details
Published in:American scientist 1993-11, Vol.81 (6), p.507
Main Author: Hutton, Larrie V
Format: Article
Language:English
Subjects:
Analysis
Artificial neural networks
Computer networks
Electromagnetic noise
Measurement
Methods
Neural networks
Statistics
Statistics (Data)
Online Access:Get full text
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Summary:Statistical noise data analysis methods include neural-network techniques that are useful statistical tools for historical-data-based judgment. Neural-network statistical properties include noise-tolerance, data overfitting minimization and proper model accuracy-size balance. Neural-networks are yet to gain wide acceptance as useful statistical tools.
ISSN:0003-0996