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Most multilayer networks are trained using the back propagation (BP) algorithm for forecasting.
All networks are trained using the whole set of training data for all the considered models.
In the training part, K SVMs are trained using the data of the training set.
In all configurations, the acoustic models are trained using the modified feature space.
Linear SVM's are used during the learning process and are trained using the target and transformed source.
After that, K SBL models are trained using the SVM forecast results and the corresponding NWP data.
Similar(31)
RF were trained using the RandomForestClassifier.
The system was trained using the phonetically balanced sentences database.
The network has been trained using the back-propagation algorithm.
The models were trained using the machine learning library LIBSVM.
The SI model was trained using the following configurations.
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