/**
   * Determine the ideal fields.
   *
   * @param headerList The headers.
   * @return The indexes of the ideal fields.
   */
  private int[] determineIdealFields(final CSVHeaders headerList) {

    int[] result;
    final String type = getProp().getPropertyString(ScriptProperties.ML_CONFIG_TYPE);

    // is it non-supervised?
    if (type.equals(MLMethodFactory.TYPE_SOM)) {
      result = new int[0];
      return result;
    }

    final List<Integer> fields = new ArrayList<Integer>();

    for (int currentIndex = 0; currentIndex < headerList.size(); currentIndex++) {
      final String baseName = headerList.getBaseHeader(currentIndex);
      final int slice = headerList.getSlice(currentIndex);
      final AnalystField field = getAnalyst().getScript().findNormalizedField(baseName, slice);

      if (field != null && field.isOutput()) {
        fields.add(currentIndex);
      }
    }

    // allocate result array
    result = new int[fields.size()];
    for (int i = 0; i < result.length; i++) {
      result[i] = fields.get(i);
    }

    return result;
  }
  /**
   * Determine the input fields.
   *
   * @param headerList The headers.
   * @return The indexes of the input fields.
   */
  private int[] determineInputFields(final CSVHeaders headerList) {
    final List<Integer> fields = new ArrayList<Integer>();

    for (int currentIndex = 0; currentIndex < headerList.size(); currentIndex++) {
      final String baseName = headerList.getBaseHeader(currentIndex);
      final int slice = headerList.getSlice(currentIndex);
      final AnalystField field = getAnalyst().getScript().findNormalizedField(baseName, slice);

      if (field != null && field.isInput()) {
        fields.add(currentIndex);
      }
    }

    // allocate result array
    final int[] result = new int[fields.size()];
    for (int i = 0; i < result.length; i++) {
      result[i] = fields.get(i);
    }

    return result;
  }