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The network has been trained using the back-propagation algorithm.
This network has been trained using the Levenberg-Marquardt back-propagation algorithm by MATLAB environment, like the presented network for densities.
On the other hand, the uniform unigram LM has been trained using the training input dictionary created with the material provided by the organizers.
As of December 1997, at least 5 300 extension workers had been trained using the two training modules developed by the project.
Models 3 and 4 have been trained using the ICs classified by residue type (polarity in Model 3, hydrophobicity in Model 4).
throughout, and had been trained using the technique of forward chaining with a clicker and a food reward (Educ Royal Canin®).
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The ANN was trained using the back propagation algorithm.
The neural-network predictor is trained using the REST tool.
Different ANNs were trained using the backpropagation learning algorithm.
Each network was trained using the extracted training patches and their class labels as inputs.
The NN model is trained using the results from the HNM.
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