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US 2011/0087627 A1Published application
Using neural network confidence to improve prediction accuracy
AssigneeGeneral Electric Company
InventorsJames J. Schmid, Danni David
Life of this patent
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Abstract
Systems and methods may be provided for generating a prediction using neural networks. The system and methods may include training a plurality of neural networks with training data, calculating an output value for each of the plurality of neural networks based at least in part on input evaluation points, applying a weight to each output value based at least in part on a confidence value for each of the plurality of neural networks; and generating an output result.
Claims20
A method for generating a prediction using neural networks, the method comprising:
- training a plurality of neural networks with training data;
- calculating an output value for each of the plurality of neural networks based at least in part on input evaluation points;
- applying a weight to each output value based at least in part on a confidence value for each of the plurality of neural networks;
- and
- generating an output result.
2 more elements
A prediction system comprising:
- at least one processor operable to:
- train a plurality of neural networks with training data;
- calculate an output value for each of the plurality of neural networks based at least in part on input evaluation points;
- apply a weight to each output value based at least in part on a confidence value for each of the plurality of neural networks;
- and
- generate an output result.
3 more elements
A prediction system comprising:
- at least one processor operable to:
- train a plurality of neural networks with training data;
- calculate an output value for each of the plurality of neural networks based at least in part on input evaluation points;
- apply a weight to each output value based at least in part on a confidence value for each of the plurality of neural networks;
- sum the weighted output values;
- sum the weights;
- divide the summed weighted output values by the summed weights;
- and
- generate an output result.
6 more elements
Dependencies are inferred from the claim text.