Package org.encog.neural.networks

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

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    } while(train.getError() > 0.01);

    // test the neural network
    System.out.println("Neural Network Results:");
    for(MLDataPair pair: trainingSet ) {
      final MLData output = network.compute(pair.getInput());
      System.out.println(pair.getInput().getData(0) + "," + pair.getInput().getData(1)
          + ", actual=" + output.getData(0) + ",ideal=" + pair.getIdeal().getData(0));
    }
  }
}
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    } while(train.getError() > 0.01);

    // test the neural network
    System.out.println("Neural Network Results:");
    for(MLDataPair pair: trainingSet ) {
      final MLData output = network.compute(pair.getInput());
      System.out.println(pair.getInput().getData(0) + "," + pair.getInput().getData(1)
          + ", actual=" + output.getData(0) + ",ideal=" + pair.getIdeal().getData(0));
    }
  }
}
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    prune.changeNeuronCount(1, 60);
   
    BasicMLData input = new BasicMLData(5);
    BasicNetwork model = EncogUtility.simpleFeedForward(5,60,0,2,true);
    checkWithModel(model.getStructure().getFlat(),network.getStructure().getFlat());
    model.compute(input);
    network.compute(input);
  }
 
  public void testRandomizeNeuronInput()
  {
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