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
Link To Document :
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