src/core/network/NeuralNetwork.java
public MMatrix predict(MMatrix input) throws NeuralNetworkException, MatrixException {
        if (input == null) throw new NeuralNetworkException("No prediction inputs set");
        Sequence inputs = new Sequence(input.getDepth());
        inputs.put(0, input);
        return predict(inputs, true).get(0);
    }
/**
     * Predicts values based on given input.
     *
     * @param input input for prediction.
     * @return predicted value (neural network output).
     * @throws NeuralNetworkException throws exception if prediction fails.
     * @throws MatrixException throws exception if depth of matrix is less than 1.
     */
Predicts values based on given input.
@param input input for prediction.
@return predicted value (neural network output).
@throws NeuralNetworkException throws exception if prediction fails.
@throws MatrixException throws exception if depth of matrix is less than 1.
Predicts values based on given input . @param input input for prediction . @return predicted value ( neural network output ) . @throws NeuralNetworkException throws exception if prediction fails . @throws MatrixException throws exception if depth of matrix is less than 1 .
public MMatrix predict(MMatrix input) throws NeuralNetworkException, MatrixException {
        if (input == null) throw new NeuralNetworkException("No prediction inputs set");
        Sequence inputs = new Sequence(input.getDepth());
        inputs.put(0, input);
        return predict(inputs, true).get(0);
    }
public MMatrix predict ( MMatrix input ) throws NeuralNetworkException , MatrixException { if ( input == null ) throw new NeuralNetworkException ( "No prediction inputs set" ) ; Sequence inputs = new Sequence ( input . getDepth ( ) ) ; inputs . put ( 0 , input ) ; return predict ( inputs , true ) . get ( 0 ) ; }
Predicts values based on given input.
Predicts values based on given input .