Examples of dumpWeights()

Examples of org.encog.neural.networks.BasicNetwork.dumpWeights()

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    double[] d = { 0,0,0,0,0,0,0,0,0,0,0,0,0 };
    BasicNetwork network = EncogUtility.simpleFeedForward(2,3,0,1,false);
    NetworkCODEC.arrayToNetwork(d, network);
    PruneSelective prune = new PruneSelective(network);
    prune.randomizeNeuron(100, 100, 0,1);
    Assert.assertEquals("0,0,0,0,0,100,0,0,100,0,0,100,0", network.dumpWeights());
  }
 
  public void testRandomizeNeuronHidden()
  {
    double[] d = { 0,0,0,0,0,0,0,0,0,0,0,0,0 };
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Examples of org.encog.neural.networks.BasicNetwork.dumpWeights()

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    double[] d = { 0,0,0,0,0,0,0,0,0,0,0,0,0 };
    BasicNetwork network = EncogUtility.simpleFeedForward(2,3,0,1,false);
    NetworkCODEC.arrayToNetwork(d, network);
    PruneSelective prune = new PruneSelective(network);
    prune.randomizeNeuron(100, 100, 1,1);
    Assert.assertEquals("0,100,0,0,0,0,0,100,100,100,0,0,0", network.dumpWeights());
  }
 
  public void testRandomizeNeuronOutput()
  {
    double[] d = { 0,0,0,0,0,0,0,0,0,0,0,0,0 };
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Examples of org.encog.neural.networks.BasicNetwork.dumpWeights()

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    double[] d = { 0,0,0,0,0,0,0,0,0,0,0,0,0 };
    BasicNetwork network = EncogUtility.simpleFeedForward(2,3,0,1,false);
    NetworkCODEC.arrayToNetwork(d, network);
    PruneSelective prune = new PruneSelective(network);
    prune.randomizeNeuron(100, 100, 2,0);
    Assert.assertEquals("100,100,100,100,0,0,0,0,0,0,0,0,0", network.dumpWeights());
  }
}
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