Added comments to ExampleSine
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1 changed files with 14 additions and 2 deletions
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@ -18,19 +18,26 @@ public class ExampleSine {
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private static final int TEST_SIZE = 1000;
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public static void main(String[] args) {
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// training set
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SimpleMatrix[] X_train = new SimpleMatrix[TRAINING_SIZE];
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SimpleMatrix[] y_train = new SimpleMatrix[TRAINING_SIZE];
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// test set
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SimpleMatrix[] X_test = new SimpleMatrix[TEST_SIZE];
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SimpleMatrix[] y_test = new SimpleMatrix[TEST_SIZE];
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// identical test set for plotting
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double[] X_test_linspace = Utilities.linspace(0, 2 * Math.PI, TEST_SIZE);
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double[] y_test_true = new double[TEST_SIZE];
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double[] y_test_pred = new double[TEST_SIZE];
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SimpleMatrix[] X_test = new SimpleMatrix[TEST_SIZE];
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SimpleMatrix[] y_test = new SimpleMatrix[TEST_SIZE];
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Random random = new Random();
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// generate training set from random data
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for (int i = 0; i < TRAINING_SIZE; i++) {
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double temp = random.nextDouble(0, 2 * Math.PI);
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X_train[i] = new SimpleMatrix(new double[][]{{temp}});
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y_train[i] = new SimpleMatrix(new double[][]{{Math.sin(temp)}});
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}
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// generate test set
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for (int i = 0; i < TEST_SIZE; i++) {
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X_test[i] = new SimpleMatrix(new double[][]{{X_test_linspace[i]}});
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y_test[i] = new SimpleMatrix(new double[][]{{Math.sin(X_test_linspace[i])}});
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@ -45,9 +52,13 @@ public class ExampleSine {
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network.addLayer(new ActivationLayer(ActivationFunctions::LeakyReLu, ActivationFunctions::LeakyReLuPrime));
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network.addLayer(new FCLayer(1));
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// configure loss function for the network
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network.use(LossFunctions::MSE, LossFunctions::MSEPrime);
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// train network on X_train and y_train
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network.fit(X_train, y_train, 100, 0.05d);
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// predict X_test and output results to console
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SimpleMatrix[] output = network.predict(X_test);
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for (int i = 0; i < output.length; i++) {
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y_test_pred[i] = output[i].get(0);
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@ -58,6 +69,7 @@ public class ExampleSine {
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System.out.println();
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}
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// create and display chart
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XYChart chart = new XYChartBuilder().title("sin(x) predictions").xAxisTitle("x").yAxisTitle("y").build();
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chart.addSeries("sin(x) true", X_test_linspace, y_test_true);
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chart.addSeries("sin(x) predictions", X_test_linspace, y_test_pred);
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