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java.lang.Objectbe.ac.ulb.mlg.utils.measure.BrownCorrelation
public class BrownCorrelation
Jump up to: a b c Szkely, Rizzo and Bakirov (2007) Jump up to: a b c d Szkely & Rizzo (2009) http://en.wikipedia.org/wiki/Distance_correlation#Distance_correlation The used strategy to handle missing value is to evaluate values with all available value (estimate means) and try to infer the covariance
Field Summary |
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Fields inherited from interface be.ac.ulb.mlg.utils.Measure |
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ERROR_VALUE |
Constructor Summary | |
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BrownCorrelation()
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Method Summary | |
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boolean |
hasNativeImplementation()
Know if the measure owns a native implementation |
static void |
main(String[] args)
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double |
measure(double[] a,
double[] b,
boolean[] computable)
Compute the measure between two data vectors |
boolean |
requireDataTransformation()
Know if the measure need to transform input data (input data are copied to be preserved) |
void |
transform(double[][] data)
The transformation method called before measurement |
Methods inherited from class java.lang.Object |
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equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
Constructor Detail |
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public BrownCorrelation()
Method Detail |
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public double measure(double[] a, double[] b, boolean[] computable)
Measure
measure
in interface Measure
a
- The first data vectorb
- The second data vectorcomputable
- Boolean vector set to true except for indexes they must be ignored during the measurement
public static void main(String[] args)
public boolean hasNativeImplementation()
Measure
hasNativeImplementation
in interface Measure
public boolean requireDataTransformation()
Measure
requireDataTransformation
in interface Measure
public void transform(double[][] data)
Measure
transform
in interface Measure
data
- An input data vector to be measured
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