Uses of Class
tutorial.clustering.SameSizeKMeans.Meta
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Packages that use SameSizeKMeans.Meta Package Description tutorial.clustering Classes from the tutorial on implementing a custom k-means variation. -
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Uses of SameSizeKMeans.Meta in tutorial.clustering
Fields in tutorial.clustering declared as SameSizeKMeans.Meta Modifier and Type Field Description (package private) SameSizeKMeans.Meta
SameSizeKMeans.PreferenceComparator. c
Meta to use for comparison.Methods in tutorial.clustering that return types with arguments of type SameSizeKMeans.Meta Modifier and Type Method Description protected WritableDataStore<SameSizeKMeans.Meta>
SameSizeKMeans. initializeMeta(Relation<V> relation, double[][] means)
Initialize the metadata storage.Methods in tutorial.clustering with parameters of type SameSizeKMeans.Meta Modifier and Type Method Description it.unimi.dsi.fastutil.ints.IntComparator
SameSizeKMeans.PreferenceComparator. select(SameSizeKMeans.Meta c)
Set the meta to sort byprotected void
SameSizeKMeans. transfer(WritableDataStore<SameSizeKMeans.Meta> metas, SameSizeKMeans.Meta meta, ModifiableDBIDs src, ModifiableDBIDs dst, DBIDRef id, int dstnum)
Transfer a single element from one cluster to another.Method parameters in tutorial.clustering with type arguments of type SameSizeKMeans.Meta Modifier and Type Method Description protected ArrayModifiableDBIDs
SameSizeKMeans. initialAssignment(java.util.List<ModifiableDBIDs> clusters, WritableDataStore<SameSizeKMeans.Meta> metas, DBIDs ids)
protected double[][]
SameSizeKMeans. refineResult(Relation<V> relation, double[][] means, java.util.List<ModifiableDBIDs> clusters, WritableDataStore<SameSizeKMeans.Meta> metas, ArrayModifiableDBIDs tids)
Perform k-means style iterations to improve the clustering result.protected void
SameSizeKMeans. transfer(WritableDataStore<SameSizeKMeans.Meta> metas, SameSizeKMeans.Meta meta, ModifiableDBIDs src, ModifiableDBIDs dst, DBIDRef id, int dstnum)
Transfer a single element from one cluster to another.protected void
SameSizeKMeans. updateDistances(Relation<V> relation, double[][] means, WritableDataStore<SameSizeKMeans.Meta> metas, NumberVectorDistance<? super V> df)
Compute the distances of each object to all means.
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