Method for accommodating missing descriptor and property data while training neural network models
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United States of America Patent
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Issued Date -
Sep 23, 2004
app pub date -
Dec 19, 2003
filing date -
Dec 20, 2002
priority date (Note) -
Abandoned
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Abstract
Systems and methods are described for training a neural network with a set of training items that contains items missing one or more X descriptors and/or one or more Y property values. Missing property values are accommodated by not back propagating error due to predictions of the missing property values. Missing descriptors are accommodated by first providing initial estimates for the missing descriptors. The missing descriptors are predicted in replicated output nodes along with properties of interest. Error is then back propagated all the way to the missing descriptor input nodes in order to adjust the estimates. Iteration can provide optimized estimates of the missing descriptors along with an optimized neural network. Missing descriptors in new items whose properties of interest are to be predicted can similarly be accommodated.
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