src/core/network/NeuralNetwork.java
private void trainIterations() throws MatrixException, IOException, NeuralNetworkException, DynamicParamException {
        trainingSampler.reset();
        int numberOfIterations = trainingSampler.getNumberOfIterations();
        for (int iteration = 0; iteration < numberOfIterations; iteration++) {
            trainIteration();
            if (stoppedExecution()) break;
            if (earlyStopping != null) if (earlyStopping.stopTraining()) break;
        }
        stateCompleted();
    }
/**
     * Trains neural network with defined number of iterations.
     *
     * @throws MatrixException throws exception if matrix operation fails.
     * @throws IOException throws exception if neural network persistence operation fails.
     * @throws NeuralNetworkException throws exception if neural network training fails.
     * @throws DynamicParamException throws exception if parameter (params) setting fails.
     */
Trains neural network with defined number of iterations.
@throws MatrixException throws exception if matrix operation fails.
@throws IOException throws exception if neural network persistence operation fails.
@throws NeuralNetworkException throws exception if neural network training fails.
@throws DynamicParamException throws exception if parameter (params) setting fails.
Trains neural network with defined number of iterations . @throws MatrixException throws exception if matrix operation fails . @throws IOException throws exception if neural network persistence operation fails . @throws NeuralNetworkException throws exception if neural network training fails . @throws DynamicParamException throws exception if parameter ( params ) setting fails .
private void trainIterations() throws MatrixException, IOException, NeuralNetworkException, DynamicParamException {
        trainingSampler.reset();
        int numberOfIterations = trainingSampler.getNumberOfIterations();
        for (int iteration = 0; iteration < numberOfIterations; iteration++) {
            trainIteration();
            if (stoppedExecution()) break;
            if (earlyStopping != null) if (earlyStopping.stopTraining()) break;
        }
        stateCompleted();
    }
private void trainIterations ( ) throws MatrixException , IOException , NeuralNetworkException , DynamicParamException { trainingSampler . reset ( ) ; int numberOfIterations = trainingSampler . getNumberOfIterations ( ) ; for ( int iteration = 0 ; iteration < numberOfIterations ; iteration ++ ) { trainIteration ( ) ; if ( stoppedExecution ( ) ) break ; if ( earlyStopping != null ) if ( earlyStopping . stopTraining ( ) ) break ; } stateCompleted ( ) ; }
Trains neural network with defined number of iterations.
Trains neural network with defined number of iterations .