AIMA.Core.Learning.Neural.FeedForwardNeuralNetwork.testOnDataSet C# (CSharp) Method

	public int[] testOnDataSet(NNDataSet nnds) {
		int[] result = new int[] { 0, 0 };
		nnds.refreshDataset();
		while (nnds.hasMoreExamples()) {
			NNExample nne = nnds.getExampleAtRandom();
			Vector prediction = predict(nne);
			if (nne.isCorrect(prediction)) {
				result[0] = result[0] + 1;
			} else {
				result[1] = result[1] + 1;
			}
		}
		return result;
	}

        public void testDataSetPopulation()
        {
            DataSet irisDataSet = DataSetFactory.getIrisDataSet();
            Numerizer numerizer = new IrisDataSetNumerizer();
            NNDataSet innds = new IrisNNDataSet();

            innds.createExamplesFromDataSet(irisDataSet, numerizer);

            NNConfig config = new NNConfig();
            config.setConfig(FeedForwardNeuralNetwork.NUMBER_OF_INPUTS, 4);
            config.setConfig(FeedForwardNeuralNetwork.NUMBER_OF_OUTPUTS, 3);
            config.setConfig(FeedForwardNeuralNetwork.NUMBER_OF_HIDDEN_NEURONS, 6);
            config.setConfig(FeedForwardNeuralNetwork.LOWER_LIMIT_WEIGHTS, -2.0);
            config.setConfig(FeedForwardNeuralNetwork.UPPER_LIMIT_WEIGHTS, 2.0);

            FeedForwardNeuralNetwork ffnn = new FeedForwardNeuralNetwork(config);
            ffnn.setTrainingScheme(new BackPropLearning(0.1, 0.9));

            ffnn.trainOn(innds, 10);

            innds.refreshDataset();
            ffnn.testOnDataSet(innds);
        }