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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