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KMeansClusterCollection Properties |
The KMeansClusterCollection type exposes the following members.
Properties| Name | Description | |
|---|---|---|
 | Centroids |
Gets or sets the clusters' centroids.
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| Clusters |
Gets the collection of clusters currently modeled by the clustering algorithm.
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| Count |
Gets the number of clusters in the collection.
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| Covariances |
Gets the clusters' variance-covariance matrices.
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| Dimension | Obsolete.
Gets the dimensionality of the data space.
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| Distance |
Gets or sets the distance function used to measure the distance
between a point and the cluster centroid in this clustering definition.
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| Item |
Gets the KMeansClusterCollectionKMeansCluster at the specified index.
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| NumberOfClasses |
Gets the number of classes expected and recognized by the classifier.
(Inherited from ClassifierBaseTInput, TClasses.) |
| NumberOfInputs |
Gets the number of inputs accepted by the model.
(Inherited from TransformBaseTInput, TOutput.) |
| NumberOfOutputs |
Gets the number of outputs generated by the model.
(Inherited from TransformBaseTInput, TOutput.) |
| Proportions |
Gets the proportion of samples in each cluster.
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See Also