Examples of generate()

Examples of org.encog.neural.pattern.FeedForwardPattern.generate()

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    FeedForwardPattern pattern = new FeedForwardPattern();
    pattern.setInputNeurons(this.input[0].length);
    pattern.setOutputNeurons(this.ideal[0].length);
    pattern.addHiddenLayer(8);
    pattern.setActivationFunction(new ActivationSigmoid());
    return (BasicNetwork)pattern.generate();
  }
   
  public BasicNetwork createJordan()
  {
    JordanPattern pattern = new JordanPattern();
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Examples of org.encog.neural.pattern.HopfieldPattern.generate()

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    CreateHopfieldDialog dialog = new CreateHopfieldDialog(EncogWorkBench
        .getInstance().getMainWindow());
    if (dialog.process()) {
      HopfieldPattern hopfield = new HopfieldPattern();
      hopfield.setInputNeurons(dialog.getNeuronCount().getValue());
      return hopfield.generate();
    } else
      return null;
  }

  private static MLMethod createSOM() {
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Examples of org.encog.neural.pattern.JordanPattern.generate()

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    JordanPattern pattern = new JordanPattern();
    pattern.setInputNeurons(this.input[0].length);
    pattern.setOutputNeurons(this.ideal[0].length);
    pattern.addHiddenLayer(16);
    pattern.setActivationFunction(new ActivationSigmoid());
    return (BasicNetwork)pattern.generate();
  }
 
  public void run()
  {
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Examples of org.encog.neural.pattern.PNNPattern.generate()

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      PNNPattern pattern = new PNNPattern();
      pattern.setInputNeurons(dialog.getInputCount().getValue());
      pattern.setOutputNeurons(dialog.getOutputCount().getValue());
      pattern.setKernel(dialog.getKernelType());
      pattern.setOutmodel(dialog.getOutputModel());
      return pattern.generate();
    }
    return null;
  }

  private static MLMethod createSVM() {
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Examples of org.encog.neural.pattern.RadialBasisPattern.generate()

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        int numNeurons = (int)Math.pow(numNeuronsPerDimension, dimensions);
        int numEdges = (int)(dimensions * Math.pow(2, dimensions - 1));

        pattern.addHiddenLayer(numNeurons);

        RBFNetwork network = (RBFNetwork)pattern.generate();

        //Position the multidimensional RBF neurons, with equal spacing, within the provided sample space from 0 to 1.
        network.setRBFCentersAndWidthsEqualSpacing(0, 1, RBFEnum.Gaussian, volumeNeuronWidth, includeEdgeRBFs);

        //Create some training data that can not easily be represented by gaussians
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Examples of org.encog.neural.pattern.SOMPattern.generate()

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        .getInstance().getMainWindow());
    if (dialog.process()) {
      SOMPattern som = new SOMPattern();
      som.setInputNeurons(dialog.getInputCount().getValue());
      som.setOutputNeurons(dialog.getOutputCount().getValue());
      return som.generate();
    } else
      return null;
  }

  private static MLMethod createFeedForward() {
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Examples of org.encog.neural.pattern.SVMPattern.generate()

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      SVMPattern svm = new SVMPattern();
      svm.setInputNeurons(dialog.getInputCount().getValue());
      svm.setOutputNeurons(dialog.getOutputCount().getValue());
      svm.setKernelType(dialog.getKernelType());
      svm.setSVMType(dialog.getSVMType());
      return svm.generate();
    } else
      return null;
  }

 
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Examples of org.encog.workbench.util.TemporalXOR.generate()

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      } catch (NumberFormatException e) {
        EncogWorkBench.displayError("Error",
            "Must enter a valid number.");
      }
      TemporalXOR temp = new TemporalXOR();
      BasicMLDataSet trainingData = (BasicMLDataSet) temp
          .generate(count);
      File targetFile = new File(EncogWorkBench.getInstance()
          .getProjectDirectory(), name);
      EncogUtility.saveCSV(targetFile, CSVFormat.ENGLISH, trainingData);
    }
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Examples of org.erlide.annotations.MultipleParameterMethodMemoizer.generate()

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            _singleParameterMethodMemoizer.generate();
            break;
          default:
            int _indexOf_2 = methods.indexOf(it);
            MultipleParameterMethodMemoizer _multipleParameterMethodMemoizer = new MultipleParameterMethodMemoizer(it, context, _indexOf_2);
            _multipleParameterMethodMemoizer.generate();
            break;
        }
      }
    };
    IterableExtensions.forEach(methods, _function);
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Examples of org.erlide.annotations.ParamterlessMethodMemoizer.generate()

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        int _size = IterableExtensions.size(_parameters);
        switch (_size) {
          case 0:
            int _indexOf = methods.indexOf(it);
            ParamterlessMethodMemoizer _paramterlessMethodMemoizer = new ParamterlessMethodMemoizer(it, context, _indexOf);
            _paramterlessMethodMemoizer.generate();
            break;
          case 1:
            int _indexOf_1 = methods.indexOf(it);
            SingleParameterMethodMemoizer _singleParameterMethodMemoizer = new SingleParameterMethodMemoizer(it, context, _indexOf_1);
            _singleParameterMethodMemoizer.generate();
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