O
- Object typeD
- Distance type@Reference(title="Subsampling for Efficient and Effective Unsupervised Outlier Detection Ensembles", authors="A. Zimek and M. Gaudet and R. J. G. B. Campello and J. Sander", booktitle="Proc. 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD \'13") public class RandomSampleKNNPreprocessor<O,D extends Distance<D>> extends AbstractMaterializeKNNPreprocessor<O,D,KNNList<D>>
Subsampling for Efficient and Effective Unsupervised Outlier Detection
Ensembles
A. Zimek and M. Gaudet and R. J. G. B. Campello and J. Sander
In: Proc. 19th ACM SIGKDD International Conference on Knowledge Discovery and
Data Mining, KDD '13
Modifier and Type | Class and Description |
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static class |
RandomSampleKNNPreprocessor.Factory<O,D extends Distance<D>>
The parameterizable factory.
|
Modifier and Type | Field and Description |
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private static Logging |
LOG
Logger
|
private RandomFactory |
rnd
Random generator
|
private double |
share
Relative share of objects to get
|
distanceFunction, distanceQuery, k
storage
relation
Constructor and Description |
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RandomSampleKNNPreprocessor(Relation<O> relation,
DistanceFunction<? super O,D> distanceFunction,
int k,
double share,
RandomFactory rnd)
Constructor.
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Modifier and Type | Method and Description |
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protected Logging |
getLogger()
Get the classes static logger.
|
String |
getLongName()
A "pretty" name for the result, for use in titles, captions and menus.
|
String |
getShortName()
A short name for the result, useful for file names.
|
void |
logStatistics()
Send statistics to the logger, if enabled.
|
protected void |
preprocess()
Perform the preprocessing step.
|
createStorage, get, getDistanceFactory, getDistanceQuery, getK, getKNNQuery, initialize
private static final Logging LOG
private final double share
private final RandomFactory rnd
public RandomSampleKNNPreprocessor(Relation<O> relation, DistanceFunction<? super O,D> distanceFunction, int k, double share, RandomFactory rnd)
relation
- Relation to indexdistanceFunction
- distance functionk
- kshare
- Relative sharernd
- Random generatorprotected void preprocess()
AbstractMaterializeKNNPreprocessor
preprocess
in class AbstractMaterializeKNNPreprocessor<O,D extends Distance<D>,KNNList<D extends Distance<D>>>
protected Logging getLogger()
AbstractPreprocessorIndex
public String getLongName()
Result
getLongName
in interface Result
getLongName
in class AbstractIndex<O>
public String getShortName()
Result
getShortName
in interface Result
getShortName
in class AbstractIndex<O>
public void logStatistics()
Index