@Test public void testGetNetOutputSize(){ assertEquals("The size of the network output is not as expected.", NET_TOPOLOGY[NET_TOPOLOGY.length - 1], neuralNet.getNetOutputSize()); }
public int getNetOutputSize() { return netOutputDim; }
BasicNeuralNet implements NeuralNet, Serializable { public int getNetOutputSize() { return netOutputDim; } }
BasicNeuralNet implements NeuralNet, Serializable { public int getNetOutputSize() { return netOutputDim; } BasicNeuralNet(int[] netTopology, double biasInput,
            Class<? extends ActivationFunction> activationFunction, Random random); }
BasicNeuralNet implements NeuralNet, Serializable { public int getNetOutputSize() { return netOutputDim; } BasicNeuralNet(int[] netTopology, double biasInput,
            Class<? extends ActivationFunction> activationFunction, Random random); List<Neuron> getLayerUnits(int layerIndex); int getLayersCount(); double[] feedForward(final double[] inputPattern); double[] getOutput(); void reset(); int getNetInputSize(); int getNetOutputSize(); }
BasicNeuralNet implements NeuralNet, Serializable { public int getNetOutputSize() { return netOutputDim; } BasicNeuralNet(int[] netTopology, double biasInput,
            Class<? extends ActivationFunction> activationFunction, Random random); List<Neuron> getLayerUnits(int layerIndex); int getLayersCount(); double[] feedForward(final double[] inputPattern); double[] getOutput(); void reset(); int getNetInputSize(); int getNetOutputSize();  }