Examples of InputFieldMLDataSet

Examples of org.encog.util.normalize.input.InputFieldMLDataSet

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    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));
        
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Examples of org.encog.util.normalize.input.InputFieldMLDataSet

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    } else if (field instanceof InputFieldCSV) {
      final InputFieldCSV fieldCSV = (InputFieldCSV) field;
      final ReadCSV csv = this.csvMap.get(field);
      result = csv.getDouble(fieldCSV.getOffset());
    } else if (field instanceof InputFieldMLDataSet) {
      final InputFieldMLDataSet neuralField =
        (InputFieldMLDataSet) field;
      final MLDataFieldHolder holder = this.dataSetFieldMap
          .get(field);
      final MLDataPair pair = holder.getPair();
      int offset = neuralField.getOffset();
      if (offset < pair.getInput().size()) {
        result = pair.getInput().getData(offset);
      } else {
        offset -= pair.getInput().size();
        result = pair.getIdeal().getData(offset);
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Examples of org.encog.util.normalize.input.InputFieldMLDataSet

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      new HashMap<MLDataSet, MLDataFieldHolder>();

    // find the unique files
    for (final InputField field : this.inputFields) {
      if (field instanceof InputFieldMLDataSet) {
        final InputFieldMLDataSet dataSetField =
          (InputFieldMLDataSet) field;
        final MLDataSet dataSet = dataSetField.getNeuralDataSet();
        if (!uniqueSets.containsKey(dataSet)) {
          final Iterator<MLDataPair> iterator = dataSet
              .iterator();
          final MLDataFieldHolder holder =
            new MLDataFieldHolder(
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Examples of org.encog.util.normalize.input.InputFieldMLDataSet

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    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));
    return norm;
  }
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