Uses of Package
org.apache.mahout.clustering

Packages that use org.apache.mahout.clustering
org.apache.mahout.clustering  
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   
org.apache.mahout.clustering.topdown.postprocessor   
 

Classes in org.apache.mahout.clustering used by org.apache.mahout.clustering
AbstractCluster
           
Cluster
          Implementations of this interface have a printable representation and certain attributes that are common across all clustering implementations
ClusterClassifier
          This classifier works with any clustering Cluster.
ClusteringPolicy
          A ClusteringPolicy captures the semantics of assignment of points to clusters
ClusterObservations
           
GaussianAccumulator
           
Model
          A model is a probability distribution over observed data points and allows the probability of any data point to be computed.
WeightedVectorWritable
           
 

Classes in org.apache.mahout.clustering used by org.apache.mahout.clustering.canopy
AbstractCluster
           
Cluster
          Implementations of this interface have a printable representation and certain attributes that are common across all clustering implementations
DistanceMeasureCluster
           
Model
          A model is a probability distribution over observed data points and allows the probability of any data point to be computed.
 

Classes in org.apache.mahout.clustering used by org.apache.mahout.clustering.dirichlet
Cluster
          Implementations of this interface have a printable representation and certain attributes that are common across all clustering implementations
Model
          A model is a probability distribution over observed data points and allows the probability of any data point to be computed.
ModelDistribution
          A model distribution allows us to sample a model from its prior distribution.
 

Classes in org.apache.mahout.clustering used by org.apache.mahout.clustering.dirichlet.models
AbstractCluster
           
Cluster
          Implementations of this interface have a printable representation and certain attributes that are common across all clustering implementations
Model
          A model is a probability distribution over observed data points and allows the probability of any data point to be computed.
ModelDistribution
          A model distribution allows us to sample a model from its prior distribution.
 

Classes in org.apache.mahout.clustering used by org.apache.mahout.clustering.fuzzykmeans
AbstractCluster
           
Cluster
          Implementations of this interface have a printable representation and certain attributes that are common across all clustering implementations
ClusterObservations
           
DistanceMeasureCluster
           
Model
          A model is a probability distribution over observed data points and allows the probability of any data point to be computed.
 

Classes in org.apache.mahout.clustering used by org.apache.mahout.clustering.kmeans
AbstractCluster
           
Cluster
          Implementations of this interface have a printable representation and certain attributes that are common across all clustering implementations
ClusterObservations
           
DistanceMeasureCluster
           
 

Classes in org.apache.mahout.clustering used by org.apache.mahout.clustering.meanshift
AbstractCluster
           
Cluster
          Implementations of this interface have a printable representation and certain attributes that are common across all clustering implementations
DistanceMeasureCluster
           
Model
          A model is a probability distribution over observed data points and allows the probability of any data point to be computed.
 

Classes in org.apache.mahout.clustering used by org.apache.mahout.clustering.topdown.postprocessor
WeightedVectorWritable
           
 



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