Package org.encog.util.normalize.input

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


        throw new NormalizationError("Undefined class value: " + v);
      } else {
        result =  fieldCSV.getMappings().get(v);
      }
    } 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);
View Full Code Here


    final Map<File, ReadCSV> uniqueFiles = new HashMap<File, ReadCSV>();

    // find the unique files
    for (final InputField field : this.inputFields) {
      if (field instanceof InputFieldCSV) {
        final InputFieldCSV csvField = (InputFieldCSV) field;
        final File file = csvField.getFile();
        if (!uniqueFiles.containsKey(file)) {
          final ReadCSV csv = new ReadCSV(file.toString(), false,
              this.csvFormat);
          uniqueFiles.put(file, csv);
          this.readCSV.add(csv);
View Full Code Here

    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));
    norm.addInputField(e = new InputFieldCSV(false,FILENAME,4));
    norm.addOutputField(new OutputFieldRangeMapped(a,0.1,0.9));
    norm.addOutputField(new OutputFieldRangeMapped(b,0.1,0.9));
    norm.addOutputField(new OutputFieldRangeMapped(c,0.1,0.9));
    norm.addOutputField(new OutputFieldRangeMapped(d,0.1,0.9));
    norm.addOutputField(new OutputFieldRangeMapped(e,0.1,0.9));
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