Package de.jungblut.math.squashing

Examples of de.jungblut.math.squashing.SquaredMeanErrorFunction

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    // sample a parable of points and use one hidden layer
    MultilayerPerceptron mlp = MultilayerPerceptron.MultilayerPerceptronBuilder
        .create(
            new int[] { 2, 2, 1 },
            new ActivationFunction[] { LINEAR.get(), SIGMOID.get(),
                LINEAR.get() }, new SquaredMeanErrorFunction(), new Fmincg(),
            10000).verbose(false).build();

    // sample a parable of points
    Tuple<DoubleVector[], DoubleVector[]> sample = sampleParable();
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    // test the linear regression case
    // use a gradient descent with very small learning rate
    MultilayerPerceptron mlp = MultilayerPerceptron.MultilayerPerceptronBuilder
        .create(new int[] { 2, 1 },
            new ActivationFunction[] { LINEAR.get(), LINEAR.get() },
            new SquaredMeanErrorFunction(), new GradientDescent(1e-8, 6e-5),
            10000).verbose(false).build();

    // sample a line of points
    Tuple<DoubleVector[], DoubleVector[]> sample = sampleLinear();
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Related Classes of de.jungblut.math.squashing.SquaredMeanErrorFunction

  • de.jungblut.classification.nn.MultiLayerPerceptronTest
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