Package org.encog

Examples of org.encog.NullStatusReportable

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      NormalizationStorageArray2D target = new NormalizationStorageArray2D(arrayOutput);
     
      DataNormalization norm = new DataNormalization();
      norm.setReport(new NullStatusReportable());
      norm.setTarget(target);
      norm.addInputField(a = new InputFieldArray2D(false,ARRAY_2D,0));
      norm.addInputField(b = new InputFieldArray2D(false,ARRAY_2D,1));
      norm.addOutputField(new OutputFieldRangeMapped(a,0.1,0.9));
      norm.addOutputField(new OutputFieldRangeMapped(b,0.1,0.9));
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      RangeSegregator s;
     
      NormalizationStorageArray2D target = new NormalizationStorageArray2D(arrayOutput);
     
      DataNormalization norm = new DataNormalization();
      norm.setReport(new NullStatusReportable());
      norm.setTarget(target);
      norm.addInputField(a = new InputFieldArray2D(false,ARRAY_2D,0));
      norm.addInputField(b = new InputFieldArray2D(false,ARRAY_2D,1));
      norm.addOutputField(new OutputFieldRangeMapped(a,0.1,0.9));
      norm.addOutputField(new OutputFieldRangeMapped(b,0.1,0.9));
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      double[][] arrayOutput = new double[6][2];
     
      NormalizationStorageArray2D target = new NormalizationStorageArray2D(arrayOutput);
     
      DataNormalization norm = new DataNormalization();
      norm.setReport(new NullStatusReportable());
      norm.setTarget(target);
      norm.addInputField(a = new InputFieldArray2D(false,ARRAY_2D,0));
      norm.addInputField(b = new InputFieldArray2D(false,ARRAY_2D,1));
      norm.addOutputField(new OutputFieldRangeMapped(a,0.1,0.9));
      norm.addOutputField(new OutputFieldRangeMapped(b,0.1,0.9));
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      double[][] arrayOutput = new double[6][2];
     
      NormalizationStorageArray2D target = new NormalizationStorageArray2D(arrayOutput);
     
      DataNormalization norm = new DataNormalization();
      norm.setReport(new NullStatusReportable());
      norm.setTarget(target);
      norm.addInputField(a = new InputFieldArray2D(false,ARRAY_2D,0));
      norm.addInputField(b = new InputFieldArray2D(false,ARRAY_2D,1));
      norm.addOutputField(new OutputFieldRangeMapped(a,0.1,0.9));
      norm.addOutputField(new OutputFieldRangeMapped(b,0.1,0.9));
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    BasicNeuralDataSet dataset = new BasicNeuralDataSet(ARRAY_2D,null);
   
    NormalizationStorageArray2D target = new NormalizationStorageArray2D(arrayOutput);
   
    DataNormalization norm = new DataNormalization();
    norm.setReport(new NullStatusReportable());
    norm.setTarget(target);
    norm.addInputField(a = new InputFieldMLDataSet(false,dataset,0));
    norm.addInputField(b = new InputFieldMLDataSet(false,dataset,1));
    norm.addOutputField(new OutputFieldRangeMapped(a,0.1,0.9));
    norm.addOutputField(new OutputFieldRangeMapped(b,0.1,0.9));
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    InputField c;
    InputField d;
    InputField e;
   
    DataNormalization norm = new DataNormalization();
    norm.setReport(new NullStatusReportable());
    norm.setTarget(new NormalizationStorageCSV(FILENAME));
    norm.addInputField(a = new InputFieldArray2D(false,ARRAY_2D,0));
    norm.addInputField(b = new InputFieldArray2D(false,ARRAY_2D,1));
    norm.addInputField(c = new InputFieldArray2D(false,ARRAY_2D,2));
    norm.addInputField(d = new InputFieldArray2D(false,ARRAY_2D,3));
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    InputField c;
    InputField d;
    InputField e;
   
    DataNormalization norm = new DataNormalization();
    norm.setReport(new NullStatusReportable());
    norm.setTarget(new NormalizationStorageCSV(FILENAME));
    norm.addInputField(a = new InputFieldCSV(false,FILENAME,0));
    norm.addInputField(b = new InputFieldCSV(false,FILENAME,1));
    norm.addInputField(c = new InputFieldCSV(false,FILENAME,2));
    norm.addInputField(d = new InputFieldCSV(false,FILENAME,3));
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    double[][] arrayOutput = new double[2][4];
   
    NormalizationStorageArray2D target = new NormalizationStorageArray2D(arrayOutput);
    ZAxisGroup group = new ZAxisGroup();
    DataNormalization norm = new DataNormalization();
    norm.setReport(new NullStatusReportable());
    norm.setTarget(target);
    norm.addInputField(a = new InputFieldArray2D(false,SAMPLE1,0));
    norm.addInputField(b = new InputFieldArray2D(false,SAMPLE1,1));
    norm.addInputField(c = new InputFieldArray2D(false,SAMPLE1,2));
    norm.addOutputField(new OutputFieldZAxis(group,a));
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   * @param theCodec
   *            The codec to use.
   */
  public MemoryDataLoader(final DataSetCODEC theCodec) {
    this.codec = theCodec;
    this.status = new NullStatusReportable();
  }
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Related Classes of org.encog.NullStatusReportable

  • com.narirelays.ems.neuralnetwork.TemporalPredictionHelper
  • org.encog.app.analyst.csv.basic.BasicFile
  • org.encog.ml.data.buffer.MemoryDataLoader
  • org.encog.ml.factory.train.SVMSearchFactory
  • org.encog.util.normalize.DataNormalization
  • org.encog.util.normalize.TestMapped
  • org.encog.util.normalize.TestMultiplicative
  • org.encog.util.normalize.TestNormArray
  • org.encog.util.normalize.TestNormCSV
  • org.encog.util.normalize.TestNormDataSet
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