Models for Calculating Confidence Intervals for Neural Networks (Paperback)

This books provides the methodology of analyzing existing models to calculate confidence intervals on the results of neural networks. The three techniques for determining confidence intervals determination were the non-linear regression, the bootstrapping estimation, and the maximum likelihood estimation. The neural network used the backpropagation algorithm with an input layer, one hidden layer and an output layer with one unit. The hidden layer had a logistic or binary sigmoidal activation function and the output layer had a linear activation function. These techniques were tested on various data sets with and without additional noise. The ranges and standard deviations of the coverage probabilities over 15 simulations for the three techniques were computed.

General

Imprint:	VDM Verlag
Country of origin:	Germany
Release date:	December 2008
First published:	December 2008
Authors:	Ashutosh Nandeshwar
Dimensions:	229 x 152 x 7mm (L x W x T)
Format:	Paperback - Trade
Pages:	132
ISBN-13:	978-3-639-10548-3
Categories:	Books > Professional & Technical > Technology: general issues > Engineering: general
LSN:	3-639-10548-6
Barcode:	9783639105483

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