Neural networks for conditional probability estimation : forecasting beyond point predictions /
This volume presents a neural network architecture for the prediction of conditional probability densities - which is vital when carrying out universal approximation on variables which are either strongly skewed or multimodal. Two alternative approaches are discussed: the GM network, in which all pa...
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| Format: | eBook |
| Language: | English |
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London ; New York :
Springer,
[1999]
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| Series: | Perspectives in neural computing.
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| Online Access: | Connect to the full text of this electronic book |
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