## Uses of Interface
org.apache.mahout.clustering.Cluster

Packages that use Cluster
org.apache.mahout.clustering: This package provides several clustering algorithm implementations.
org.apache.mahout.clustering.canopy
org.apache.mahout.clustering.dirichlet
org.apache.mahout.clustering.dirichlet.models
org.apache.mahout.clustering.fuzzykmeans
org.apache.mahout.clustering.kmeans: This package provides an implementation of the k-means clustering algorithm.
org.apache.mahout.clustering.meanshift

Uses of Cluster in org.apache.mahout.clustering

Classes in org.apache.mahout.clustering that implement Cluster
`class` `AbstractCluster`
`class` `DistanceMeasureCluster`

Uses of Cluster in org.apache.mahout.clustering.canopy

Classes in org.apache.mahout.clustering.canopy that implement Cluster
`class` `Canopy` This class models a canopy as a center point, the number of points that are contained within it according to the application of some distance metric, and a point total which is the sum of all the points and is used to compute the centroid when needed.

Uses of Cluster in org.apache.mahout.clustering.dirichlet

Classes in org.apache.mahout.clustering.dirichlet that implement Cluster
`class` `DirichletCluster`

Methods in org.apache.mahout.clustering.dirichlet that return Cluster
`Cluster` `JsonClusterModelAdapter.deserialize(com.google.gson.JsonElement json, java.lang.reflect.Type typeOfT, com.google.gson.JsonDeserializationContext context)`
`Cluster` `DirichletCluster.getModel()`
`Cluster[]` `DirichletReducer.getNewModels()`
`static Cluster` `DirichletCluster.readModel(java.io.DataInput in)` Reads a typed Model instance from the input stream

Methods in org.apache.mahout.clustering.dirichlet with parameters of type Cluster
`com.google.gson.JsonElement` `JsonClusterModelAdapter.serialize(Cluster src, java.lang.reflect.Type typeOfSrc, com.google.gson.JsonSerializationContext context)`
`void` `DirichletCluster.setModel(Cluster model)`
`void` `DirichletState.update(Cluster[] newModels)` Update the receiver with the new models
`protected DirichletCluster` `DirichletClusterer.updateCluster(Cluster model, int k)`
`protected void` `DirichletClusterer.updateModels(Cluster[] newModels)`

Constructors in org.apache.mahout.clustering.dirichlet with parameters of type Cluster
`DirichletCluster(Cluster model)`
`DirichletCluster(Cluster model, double totalCount)`

Uses of Cluster in org.apache.mahout.clustering.dirichlet.models

Classes in org.apache.mahout.clustering.dirichlet.models that implement Cluster
`class` `AsymmetricSampledNormalModel`
`class` `GaussianCluster`
`class` `L1Model`
`class` `NormalModel`
`class` `SampledNormalModel`

Uses of Cluster in org.apache.mahout.clustering.fuzzykmeans

Classes in org.apache.mahout.clustering.fuzzykmeans that implement Cluster
`class` `SoftCluster`

Uses of Cluster in org.apache.mahout.clustering.kmeans

Classes in org.apache.mahout.clustering.kmeans that implement Cluster
`class` `Cluster`

Uses of Cluster in org.apache.mahout.clustering.meanshift

Classes in org.apache.mahout.clustering.meanshift that implement Cluster
`class` `MeanShiftCanopy` This class models a canopy as a center point, the number of points that are contained within it according to the application of some distance metric, and a point total which is the sum of all the points and is used to compute the centroid when needed.

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