NodeNameType
- The type used to name nodes@PublicationReference(author="Nguyen Xuan Vinh, Julien Epps, and James Bailey", title="Information Theoretic Measures of Clusterings Comparison: Variants, Properties, Normalization and Correction for Chance", type=Journal, year=2010, publication="Journal of Machine Learning Research", pages=-17) public class CommunityComparisons<NodeNameType> extends java.lang.Object
Constructor and Description |
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CommunityComparisons(NodePartitioning<NodeNameType> u,
NodePartitioning<NodeNameType> v)
Initializes this with the input partitionings of the same underlying set
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Modifier and Type | Method and Description |
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double |
getAmiMax()
Returns the max adjusted-for-chance mutual information (see Table 2 of
cited paper)
|
double |
getAmiMin()
Returns the min adjusted-for-chance mutual information (see Table 2 of
cited paper)
|
double |
getAmiSqrt()
Returns the sqrt adjusted-for-chance mutual information (see Table 2 of
cited paper)
|
double |
getAmiSum()
Returns the sum adjusted-for-chance mutual information (see Table 2 of
cited paper)
|
double |
getConditionalEntropyUGivenV()
Returns H(u|v), computing and storing it if this is the first time called
|
double |
getConditionalEntropyVGivenU()
Returns H(v|u), computing and storing it if this is the first time called
|
double |
getEntropyU()
Returns the entropy of the u partitioning (computing and storing it if
this is the first time called)
|
double |
getEntropyV()
Returns the entropy of the v partitioning (computing and storing it if
this is the first time called)
|
double |
getExpectedMutualInformation()
Returns the approximate expected value of the mutual information for the
two partitionings.
|
double |
getJointEntropy()
Returns the joint entropy (H(u,v)), computing it if this is the first
time called
|
double |
getMutualInformation()
Returns the mutual information (I(u, v)) for the two partitionings,
computing and storing it if this is the first time called
|
double |
getNmiJoint()
Returns the joint normalized mutual information (see Table 2 of cited
paper)
|
double |
getNmiMax()
Returns the max normalized mutual information (see Table 2 of cited
paper)
|
double |
getNmiMin()
Returns the min normalized mutual information (see Table 2 of cited
paper)
|
double |
getNmiSqrt()
Returns the sqrt normalized mutual information (see Table 2 of cited
paper)
|
double |
getNmiSum()
Returns the sum normalized mutual information (see Table 2 of cited
paper)
|
public CommunityComparisons(NodePartitioning<NodeNameType> u, NodePartitioning<NodeNameType> v)
u
- The first partitioningv
- The second partitioningpublic double getEntropyU()
public double getEntropyV()
public double getJointEntropy()
public double getConditionalEntropyUGivenV()
public double getConditionalEntropyVGivenU()
public double getMutualInformation()
public double getNmiJoint()
public double getNmiMax()
public double getNmiSum()
public double getNmiSqrt()
public double getNmiMin()
public double getExpectedMutualInformation()
public double getAmiMax()
public double getAmiSum()
public double getAmiSqrt()
public double getAmiMin()