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java.lang.Objectde.lmu.ifi.dbs.elki.logging.AbstractLoggable
de.lmu.ifi.dbs.elki.utilities.optionhandling.AbstractParameterizable
de.lmu.ifi.dbs.elki.math.linearalgebra.pca.CovarianceMatrixBuilder<V,D>
de.lmu.ifi.dbs.elki.math.linearalgebra.pca.WeightedCovarianceMatrixBuilder<V,D>
V
- Vector class to usepublic class WeightedCovarianceMatrixBuilder<V extends RealVector<V,?>,D extends NumberDistance<D,?>>
CovarianceMatrixBuilder
with weights.
This builder uses a weight function to weight points differently during build a covariance matrix.
Covariance can be canonically extended with weights, as shown in the article
A General Framework for Increasing the Robustness of PCA-Based Correlation Clustering Algorithms
Hans-Peter Kriegel and Peer Kröger and Erich Schubert and Arthur Zimek
In: Proc. 20th Int. Conf. on Scientific and Statistical Database Management (SSDBM), 2008, Hong Kong
Lecture Notes in Computer Science 5069, Springer
Field Summary | |
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static OptionID |
WEIGHT_ID
OptionID for WEIGHT_PARAM |
private ClassParameter<WeightFunction> |
WEIGHT_PARAM
Parameter to specify the weight function to use in weighted PCA, must implement WeightFunction . |
private DistanceFunction<V,DoubleDistance> |
weightDistance
Holds the distance function used for weight calculation |
WeightFunction |
weightfunction
Holds the weight function. |
Fields inherited from class de.lmu.ifi.dbs.elki.utilities.optionhandling.AbstractParameterizable |
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optionHandler |
Fields inherited from class de.lmu.ifi.dbs.elki.logging.AbstractLoggable |
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debug, logger |
Constructor Summary | |
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WeightedCovarianceMatrixBuilder()
Constructor, setting up parameter. |
Method Summary | |
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private double[][] |
finishCovarianceMatrix(double[] sums,
double[][] squares,
double weightsum)
Finish the Covariance matrix in array "squares". |
Matrix |
processIds(Collection<Integer> ids,
Database<V> database)
Weighted Covariance Matrix for a set of IDs. |
Matrix |
processQueryResults(Collection<DistanceResultPair<D>> results,
Database<V> database,
int k)
Compute Covariance Matrix for a QueryResult Collection By default it will just collect the ids and run processIds |
List<String> |
setParameters(List<String> args)
Parse parameters. |
Methods inherited from class de.lmu.ifi.dbs.elki.math.linearalgebra.pca.CovarianceMatrixBuilder |
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processDatabase, processQueryResults |
Methods inherited from class de.lmu.ifi.dbs.elki.utilities.optionhandling.AbstractParameterizable |
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addOption, addParameterizable, addParameterizable, checkGlobalParameterConstraints, collectOptions, getAttributeSettings, getParameters, rememberParametersExcept, removeOption, removeParameterizable, shortDescription |
Methods inherited from class de.lmu.ifi.dbs.elki.logging.AbstractLoggable |
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debugFine, debugFiner, debugFinest, exception, progress, verbose, warning |
Methods inherited from class java.lang.Object |
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clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
Field Detail |
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public static final OptionID WEIGHT_ID
WEIGHT_PARAM
private final ClassParameter<WeightFunction> WEIGHT_PARAM
WeightFunction
.
Key: -pca.weight
public WeightFunction weightfunction
private DistanceFunction<V extends RealVector<V,?>,DoubleDistance> weightDistance
Constructor Detail |
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public WeightedCovarianceMatrixBuilder()
Method Detail |
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public List<String> setParameters(List<String> args) throws ParameterException
setParameters
in interface Parameterizable
setParameters
in class AbstractParameterizable
args
- parameters to set the attributes accordingly to
ParameterException
- in case of wrong parameter-settingpublic Matrix processIds(Collection<Integer> ids, Database<V> database)
processIds
in class CovarianceMatrixBuilder<V extends RealVector<V,?>,D extends NumberDistance<D,?>>
ids
- a collection of idsdatabase
- the database used
public Matrix processQueryResults(Collection<DistanceResultPair<D>> results, Database<V> database, int k)
processQueryResults
in class CovarianceMatrixBuilder<V extends RealVector<V,?>,D extends NumberDistance<D,?>>
results
- a collection of QueryResultsdatabase
- the database usedk
- number of elements to process
private double[][] finishCovarianceMatrix(double[] sums, double[][] squares, double weightsum)
sums
- Sums of values.squares
- Sums of squares. Contents are destroyed and replaced with Covariance Matrix!weightsum
- Sum of weights.
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