![]() | KMeansClustering Class |
Namespace: CenterSpace.NMath.Core
The KMeansClustering type exposes the following members.
Name | Description | |
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![]() | KMeansClustering |
Constructs an empty KMeansClustering instance.
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![]() | KMeansClustering(DataFrame) |
Constructs a KMeansClustering instance from the given data.
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![]() | KMeansClustering(DoubleMatrix) |
Constructs a KMeansClustering instance from the given data.
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![]() | KMeansClustering(DataFrame, Int32) |
Constructs a KMeansClustering instance from the given data and the
specified maximum number of iterations.
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![]() | KMeansClustering(DoubleMatrix, Int32) |
Constructs a KMeansClustering instance from the given data and the
specified maximum number of iterations.
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Name | Description | |
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![]() | Clusters |
Gets the cluster assignments computed during the last clustering.
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![]() | Data |
Gets and sets the data matrix.
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![]() ![]() | DefaultMaxIterations |
Gets and sets the default maximum number of iterations.
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![]() | FinalCenters |
Gets the matrix of final cluster centers computed during the last clustering.
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![]() | InitialCenters |
Gets the matrix of initial cluster centers used during the last clustering.
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![]() | Iterations |
Gets the number of iterations used in the clustering just computed.
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![]() | K |
Gets the number of clusters computed during the last clustering..
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![]() | MaxIterations |
Gets and sets the maximum number of iterations used in clustering.
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![]() | MaxIterationsMet |
Returns true if the clustering just computed stopped because the
maximum number of iterations was reached; otherwise, false.
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![]() | N |
Gets the number of objects in this.Data.
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![]() | Sizes |
Gets the number of points in each cluster computed during the last clustering.
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![]() | WithinSumOfSquares |
Gets the within-cluster sum of squares for each cluster computed during the last clustering.
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Name | Description | |
---|---|---|
![]() | Clone |
Creates a deep copy of this cluster analysis.
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![]() | Cluster(Int32) |
Clusters the data into the specified number of clusters.
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![]() | Cluster(DoubleMatrix) |
Clusters the data into the specified number of clusters.
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![]() | Cluster(Int32, KMeansClusteringStart) |
Clusters the data into the specified number of clusters, using the specified method of
choosing the initial cluster centers.
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![]() | Cluster(Int32, RandGenMTwist) |
Clusters the data into the specified number of clusters.
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Name | Description | |
---|---|---|
![]() | clusters_ | The cluster assigments. |
![]() | data_ |
A matrix of data. Each row in the matrix represents an object to be clustered.
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![]() ![]() | DEFAULT_MAX_ITER | The default maximum number of iterations. |
![]() | finalCenters_ |
A matrix of final cluster centers.
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![]() | initialCenters_ |
A matrix of initial cluster centers.
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![]() | iter_ | The number of iterations performed. |
![]() | max_ | The maximum number of iterations. |
![]() | sizes_ |
The number of objects in each cluster.
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![]() | withinss_ |
The within-cluster sum of squares for each cluster.
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// cluster 8 random vectors of length 3 DoubleMatrix data = new DoubleMatrix( 8, 3, new RandGenUniform() ); KMeansClustering cl = new KMeansClustering( data ); // create 3 clusters, using random starting cluster centers ClusterSet clusters = cl.Cluster( 3 );