DocumentCode
2723982
Title
JackKnife method for validating neural network models
Author
Allred, L.G.
Author_Institution
Ogden Air Logistics Center, Hill Air Force Base, UT
fYear
1991
fDate
8-14 Jul 1991
Abstract
Summary form only given. Most methods for validating neural networks rely on the exclusion of a portion of the data throughout a portion or all of the network training process. This approach can be somewhat wasteful, particularly when the cost of samples can exceed a million dollars each. It is suggested that a more appropriate (and efficient) validation method is the JackKnife method. Although the JackKnife method was developed to validate statistical estimation procedures, it is equally applicable to the process of validating the performance of a neural network
Keywords
neural nets; JackKnife method; network training process; neural network models validation; performance; Costs; Logistics; Neural networks;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 1991., IJCNN-91-Seattle International Joint Conference on
Conference_Location
Seattle, WA
Print_ISBN
0-7803-0164-1
Type
conf
DOI
10.1109/IJCNN.1991.155456
Filename
155456
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