Neural networks adaptive boosting using semi-supervised learning

An approach for generating a trained neural network is provided. In an embodiment, a neural network, which can have an input layer, an output layer, and a hidden layer, is created. An initial training of the neural network is performed using a set of labeled data. The boosted neural network resultin...

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Hauptverfasser: Legroux, Marc Joel Herve, Hammoud, Jamal
Format: Patent
Sprache:eng
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Beschreibung
Zusammenfassung:An approach for generating a trained neural network is provided. In an embodiment, a neural network, which can have an input layer, an output layer, and a hidden layer, is created. An initial training of the neural network is performed using a set of labeled data. The boosted neural network resulting from the initial training is applied to unlabeled data to determine whether any of the unlabeled data qualifies as additional labeled data. If it is determined that any of the unlabeled data qualifies as additional labeled data, the boosted neural network is retrained using the additional labeled data. Otherwise, if it is determined that none of the unlabeled data qualifies as additional labeled data, the neural network is updated to change a number of predictor nodes in the neural network.