Class NMFConsensusMatrix uses a non-negative matrix factorization to
cluster samples.
Namespace:
CenterSpace.NMath.StatsAssembly: NMathStats (in NMathStats.dll) Version: 3.4.0.0
Syntax
| C# |
|---|
public class NMFConsensusMatrix<Alg> : ConnectivityMatrix where Alg : new(), INMFUpdateAlgorithm |
| Visual Basic (Declaration) |
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Public Class NMFConsensusMatrix(Of Alg As {New, INMFUpdateAlgorithm}) _ Inherits ConnectivityMatrix |
| Visual C++ |
|---|
generic<typename Alg> where Alg : gcnew(), INMFUpdateAlgorithm public ref class NMFConsensusMatrix : public ConnectivityMatrix |
Type Parameters
- Alg
- Update algorithm for the non-negative matrix factorization.
Remarks
Since the non-negative matrix factorization may not converge to the
same solution each time it is run, several runs are made and the
average is computed.
For each run of the clustering non-negative matrix factorization a
connectivity matrix C with cij = 1 if samples i and j belong to the
same cluster and cij = 0 if they belong to different clusters. The
consensus matrix is then computed as the average connectivity matrix
over several clustering runs. The values of the consensus matrix
range in value from 0 to 1 and reflect the probability that samples
i and j cluster together.
Inheritance Hierarchy
System..::.Object
CenterSpace.NMath.Matrix..::.DoubleSymmetricMatrix
CenterSpace.NMath.Stats..::.ConnectivityMatrix
CenterSpace.NMath.Stats..::.NMFConsensusMatrix<(Of <(Alg>)>)
CenterSpace.NMath.Matrix..::.DoubleSymmetricMatrix
CenterSpace.NMath.Stats..::.ConnectivityMatrix
CenterSpace.NMath.Stats..::.NMFConsensusMatrix<(Of <(Alg>)>)