public final class KMeansModel extends Object implements ClusterizationModel<Vector,Integer>, Exportable<KMeansModelFormat>, DeployableObject
Constructor and Description |
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KMeansModel(Vector[] centers,
DistanceMeasure distanceMeasure)
Construct KMeans model with given centers and distanceMeasure measure.
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Modifier and Type | Method and Description |
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DistanceMeasure |
distanceMeasure()
Distance measure.
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boolean |
equals(Object obj) |
int |
getAmountOfClusters()
Gets the clusters count.
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Vector[] |
getCenters()
Get cluster centers.
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List<Object> |
getDependencies()
Returns dependencies of this object that can be object with class defined by client side and unknown for server.
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int |
hashCode() |
Integer |
predict(Vector vec)
Make a prediction for the specified input arguments.
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<P> void |
saveModel(Exporter<KMeansModelFormat,P> exporter,
P path)
Save model by the given path.
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String |
toString() |
String |
toString(boolean pretty) |
public KMeansModel(Vector[] centers, DistanceMeasure distanceMeasure)
centers
- Centers.distanceMeasure
- Distance measure.public DistanceMeasure distanceMeasure()
public int getAmountOfClusters()
getAmountOfClusters
in interface ClusterizationModel<Vector,Integer>
public Vector[] getCenters()
getCenters
in interface ClusterizationModel<Vector,Integer>
public <P> void saveModel(Exporter<KMeansModelFormat,P> exporter, P path)
saveModel
in interface Exportable<KMeansModelFormat>
exporter
- Exporter.path
- Path to saved model.public String toString(boolean pretty)
toString
in interface IgniteModel<Vector,Integer>
pretty
- Use pretty mode.public List<Object> getDependencies()
getDependencies
in interface DeployableObject
GridGain In-Memory Computing Platform : ver. 8.9.14 Release Date : November 5 2024