Examples of de.lmu.ifi.dbs.elki.utilities.scaling.outlier.OutlierScalingFunction.prepare()

Package de.lmu.ifi.dbs.elki.utilities.scaling.outlier

Class de.lmu.ifi.dbs.elki.utilities.scaling.outlier.OutlierScalingFunction

Examples of de.lmu.ifi.dbs.elki.utilities.scaling.outlier.OutlierScalingFunction.prepare()

de.lmu.ifi.dbs.elki.utilities.scaling.outlier.OutlierScalingFunction.prepare()
Prepare is called once for each data set, before getScaled() will be called. This function can be used to extract global parameters such as means, minimums or maximums from the Database, Result or Annotation. @param or Outlier result to use

   * @throws IllegalStateException
   */
  protected ScoreResult computeScore(DBIDs ids, DBIDs outlierIds, OutlierResult or) throws IllegalStateException {
    if(scaling instanceof OutlierScalingFunction) {
      OutlierScalingFunction oscaling = (OutlierScalingFunction) scaling;
      oscaling.prepare(or);
    }


    final ScalingFunction innerScaling;
    // If we have useful (finite) min/max, use these for binning.
    double min = scaling.getMin();

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   * @return Result
   */
  public HistogramResult<DoubleVector> evaluateOutlierResult(Database database, OutlierResult or) {
    if(scaling instanceof OutlierScalingFunction) {
      OutlierScalingFunction oscaling = (OutlierScalingFunction) scaling;
      oscaling.prepare(or);
    }


    ModifiableDBIDs ids = DBIDUtil.newHashSet(or.getScores().getDBIDs());
    DBIDs outlierIds = DatabaseUtil.getObjectsByLabelMatch(database, positiveClassName);
    // first value for outliers, second for each object

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   * @return Result
   */
  public HistogramResult<DoubleVector> evaluateOutlierResult(Database database, OutlierResult or) {
    if(scaling instanceof OutlierScalingFunction) {
      OutlierScalingFunction oscaling = (OutlierScalingFunction) scaling;
      oscaling.prepare(or);
    }


    ModifiableDBIDs ids = DBIDUtil.newHashSet(or.getScores().getDBIDs());
    DBIDs outlierIds = DatabaseUtil.getObjectsByLabelMatch(database, positiveClassName);
    // first value for outliers, second for each object

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   * @throws IllegalStateException
   */
  protected ScoreResult computeScore(DBIDs ids, DBIDs outlierIds, OutlierResult or) throws IllegalStateException {
    if(scaling instanceof OutlierScalingFunction) {
      OutlierScalingFunction oscaling = (OutlierScalingFunction) scaling;
      oscaling.prepare(or);
    }


    final ScalingFunction innerScaling;
    // If we have useful (finite) min/max, use these for binning.
    double min = scaling.getMin();

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