コード例 #1
0
  /**
   * 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;
  }
コード例 #2
0
  /**
   * Extract fields from a file into a numeric array for machine learning.
   *
   * @param analyst The analyst to use.
   * @param headers The headers for the input data.
   * @param csv The CSV that holds the input data.
   * @param outputLength The length of the returned array.
   * @param skipOutput True if the output should be skipped.
   * @return The encoded data.
   */
  public static final double[] extractFields(
      final EncogAnalyst analyst,
      final CSVHeaders headers,
      final ReadCSV csv,
      final int outputLength,
      final boolean skipOutput) {
    final double[] output = new double[outputLength];
    int outputIndex = 0;
    for (final AnalystField stat : analyst.getScript().getNormalize().getNormalizedFields()) {

      stat.init();

      if (stat.getAction() == NormalizationAction.Ignore) {
        continue;
      }

      if (stat.isOutput() && skipOutput) {
        continue;
      }

      int index = headers.find(stat.getName());
      final String str = csv.get(index).trim();

      // is this an unknown value?
      if (str.equals("?") || str.length() == 0) {
        HandleMissingValues handler = analyst.getScript().getNormalize().getMissingValues();
        double[] d = handler.handleMissing(analyst, stat);

        // should we skip the entire row
        if (d == null) {
          return null;
        }

        // copy the returned values in place of the missing values
        for (int i = 0; i < d.length; i++) {
          output[outputIndex++] = d[i];
        }
      } else {
        // known value
        if (stat.getAction() == NormalizationAction.Normalize) {
          double d = csv.getFormat().parse(str);
          d = stat.normalize(d);
          output[outputIndex++] = d;
        } else if (stat.getAction() == NormalizationAction.PassThrough) {
          double d = csv.getFormat().parse(str);
          output[outputIndex++] = d;
        } else {
          final double[] d = stat.encode(str);
          for (final double element : d) {
            output[outputIndex++] = element;
          }
        }
      }
    }

    return output;
  }
コード例 #3
0
  /**
   * 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;
  }
コード例 #4
0
  /**
   * Write the headers.
   *
   * @param tw The output stream.
   */
  private void writeHeaders(final PrintWriter tw) {
    final StringBuilder line = new StringBuilder();
    for (final AnalystField stat : this.analyst.getScript().getNormalize().getNormalizedFields()) {
      final int needed = stat.getColumnsNeeded();

      for (int i = 0; i < needed; i++) {
        BasicFile.appendSeparator(line, getFormat());
        line.append('\"');
        line.append(CSVHeaders.tagColumn(stat.getName(), i, stat.getTimeSlice(), needed > 1));
        line.append('\"');
      }
    }
    tw.println(line.toString());
  }
コード例 #5
0
ファイル: AnalystField.java プロジェクト: hoiyoo/encog-java
  /**
   * Add headings for a raw file.
   *
   * @param line The line to write the raw headings to.
   * @param prefix The prefix to place.
   * @param format The format to use.
   */
  public final void addRawHeadings(
      final StringBuilder line, final String prefix, final CSVFormat format) {
    final int subFields = getColumnsNeeded();

    for (int i = 0; i < subFields; i++) {
      final String str = CSVHeaders.tagColumn(this.name, i, this.timeSlice, subFields > 1);
      BasicFile.appendSeparator(line, format);
      line.append('\"');
      if (prefix != null) {
        line.append(prefix);
      }
      line.append(str);
      line.append('\"');
    }
  }