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java.lang.Object de.lmu.ifi.dbs.elki.algorithm.AbstractAlgorithm<OutlierResult> de.lmu.ifi.dbs.elki.algorithm.outlier.meta.FeatureBagging
@Title(value="Feature Bagging for Outlier Detection") @Reference(title="Feature Bagging for Outlier Detection", authors="A. Lazarevic, V. Kumar", booktitle="Proc. of the 11th ACM SIGKDD international conference on Knowledge discovery in data mining", url="http://dx.doi.org/10.1145/1081870.1081891") public class FeatureBagging
A simple ensemble method called "Feature bagging" for outlier detection.
Since the proposed method is only sensible to run on multiple instances of the same algorithm (due to incompatible score ranges), we do not allow using arbitrary algorithms.
Reference:
A. Lazarevic, V. Kumar: Feature Bagging for Outlier Detection
In: Proc. of the 11th ACM SIGKDD international conference on Knowledge
discovery in data mining
Nested Class Summary | |
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static class |
FeatureBagging.Parameterizer
Parameterization class. |
Field Summary | |
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protected boolean |
breadth
Cumulative sum or breadth first combinations |
private int |
k
The parameters k for LOF. |
private static Logging |
logger
The logger for this class. |
protected int |
num
Number of instances to use |
private Random |
RANDOM
Random number generator for subspace choice |
Constructor Summary | |
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FeatureBagging(int k,
int num,
boolean breadth,
Long seed)
Constructor. |
Method Summary | |
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TypeInformation[] |
getInputTypeRestriction()
Get the input type restriction used for negotiating the data query. |
protected Logging |
getLogger()
Get the (STATIC) logger for this class. |
private BitSet |
randomSubspace(int alldim,
int mindim,
int maxdim)
Choose a random subspace |
OutlierResult |
run(Relation<NumberVector<?,?>> relation)
Run the algorithm on a data set. |
Methods inherited from class de.lmu.ifi.dbs.elki.algorithm.AbstractAlgorithm |
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makeParameterDistanceFunction, run |
Methods inherited from class java.lang.Object |
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clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
Methods inherited from interface de.lmu.ifi.dbs.elki.algorithm.outlier.OutlierAlgorithm |
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run |
Field Detail |
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private static final Logging logger
protected int num
protected boolean breadth
private Random RANDOM
private int k
Constructor Detail |
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public FeatureBagging(int k, int num, boolean breadth, Long seed)
k
- k Parameter for LOFnum
- Number of subspaces to usebreadth
- Flag for breadth-first mergingMethod Detail |
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public OutlierResult run(Relation<NumberVector<?,?>> relation)
relation
- Relation to use
private BitSet randomSubspace(int alldim, int mindim, int maxdim)
alldim
- Number of total dimensionsmindim
- Minimum number to choosemaxdim
- Maximum number to choose
protected Logging getLogger()
AbstractAlgorithm
getLogger
in class AbstractAlgorithm<OutlierResult>
public TypeInformation[] getInputTypeRestriction()
AbstractAlgorithm
getInputTypeRestriction
in interface Algorithm
getInputTypeRestriction
in class AbstractAlgorithm<OutlierResult>
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