Uses of Interface
org.apache.mahout.clustering.Model

Packages that use Model
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   
 

Uses of Model in org.apache.mahout.clustering
 

Subinterfaces of Model in org.apache.mahout.clustering
 interface Cluster
          Implementations of this interface have a printable representation and certain attributes that are common across all clustering implementations
 

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

Methods in org.apache.mahout.clustering that return Model
 Model<VectorWritable> Model.sampleFromPosterior()
           
 Model<VectorWritable> DistanceMeasureCluster.sampleFromPosterior()
           
 Model<O>[] ModelDistribution.sampleFromPosterior(Model<O>[] posterior)
          Return a list of models sampled from the posterior
 Model<O>[] ModelDistribution.sampleFromPrior(int howMany)
          Return a list of models sampled from the prior
 

Methods in org.apache.mahout.clustering with parameters of type Model
 void Model.observe(Model<O> x)
          Observe the given model, retaining information about its observations
 void AbstractCluster.observe(Model<VectorWritable> x)
           
 Model<O>[] ModelDistribution.sampleFromPosterior(Model<O>[] posterior)
          Return a list of models sampled from the posterior
 

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

Classes in org.apache.mahout.clustering.canopy that implement Model
 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 Model in org.apache.mahout.clustering.dirichlet
 

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

Methods in org.apache.mahout.clustering.dirichlet that return Model
 Model<VectorWritable>[] DirichletState.getModels()
           
 Model<VectorWritable> DirichletCluster.sampleFromPosterior()
           
protected  Model<VectorWritable>[] DirichletClusterer.samplePosteriorModels()
           
 

Methods in org.apache.mahout.clustering.dirichlet with parameters of type Model
 void DirichletCluster.observe(Model<VectorWritable> x)
           
protected  void DirichletClusterer.observe(Model<VectorWritable>[] newModels, VectorWritable observation)
           
static void DirichletCluster.writeModel(DataOutput out, Model<?> model)
          Writes a typed Model instance to the output stream
 

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

Classes in org.apache.mahout.clustering.dirichlet.models that implement Model
 class GaussianCluster
           
 

Methods in org.apache.mahout.clustering.dirichlet.models that return Model
 Model<VectorWritable> GaussianCluster.sampleFromPosterior()
           
 Model<VectorWritable>[] GaussianClusterDistribution.sampleFromPosterior(Model<VectorWritable>[] posterior)
           
 Model<VectorWritable>[] DistanceMeasureClusterDistribution.sampleFromPosterior(Model<VectorWritable>[] posterior)
           
 Model<VectorWritable>[] GaussianClusterDistribution.sampleFromPrior(int howMany)
           
 Model<VectorWritable>[] DistanceMeasureClusterDistribution.sampleFromPrior(int howMany)
           
 

Methods in org.apache.mahout.clustering.dirichlet.models with parameters of type Model
 Model<VectorWritable>[] GaussianClusterDistribution.sampleFromPosterior(Model<VectorWritable>[] posterior)
           
 Model<VectorWritable>[] DistanceMeasureClusterDistribution.sampleFromPosterior(Model<VectorWritable>[] posterior)
           
 

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

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

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

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

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

Classes in org.apache.mahout.clustering.meanshift that implement Model
 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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