Synopsis
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.
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Models for Calculating Confidence Intervals forNeural Networks
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Kartoniert / Broschiert. Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This books provides the methodology of analyzingexisting models to calculate confidence intervals onthe results of neural networks. The three techniquesfor determining confidence intervals determinationwere the non-linear regression,. Seller Inventory # 4957905
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Models for Calculating Confidence Intervals for Neural Networks | A Study
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Taschenbuch. Condition: Neu. Models for Calculating Confidence Intervals for Neural Networks | A Study | Ashutosh Nandeshwar | Taschenbuch | Kartoniert / Broschiert | Englisch | 2013 | VDM Verlag Dr. Müller | EAN 9783639105483 | Verantwortliche Person für die EU: OmniScriptum GmbH & Co. KG, Bahnhofstr. 28, 66111 Saarbrücken, info[at]akademikerverlag[dot]de | Anbieter: preigu. Seller Inventory # 101689692
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Models for Calculating Confidence Intervals for Neural Networks : A Study
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This books provides the methodology of analyzingexisting models to calculate confidence intervals onthe results of neural networks. The three techniquesfor determining confidence intervals determinationwere the non-linear regression, the bootstrappingestimation, and the maximum likelihood estimation.The neural network used the backpropagation algorithmwith an input layer, one hidden layer and an outputlayer with one unit. The hidden layer had a logisticor binary sigmoidal activation function and theoutput layer had a linear activation function. Thesetechniques were tested on various data sets with andwithout additional noise. The ranges and standarddeviations of the coverage probabilities over 15simulations for the three techniques were computed. Seller Inventory # 9783639105483