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Packages that use Cluster | |
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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 Cluster in org.apache.mahout.clustering |
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Classes in org.apache.mahout.clustering that implement Cluster | |
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class |
AbstractCluster
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class |
DistanceMeasureCluster
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Methods in org.apache.mahout.clustering that return types with arguments of type Cluster | |
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List<Cluster> |
ClusterClassifier.getModels()
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Method parameters in org.apache.mahout.clustering with type arguments of type Cluster | |
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protected void |
CIReducer.reduce(org.apache.hadoop.io.IntWritable key,
Iterable<Cluster> values,
org.apache.hadoop.mapreduce.Reducer.Context context)
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Constructor parameters in org.apache.mahout.clustering with type arguments of type Cluster | |
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ClusterClassifier(List<Cluster> models)
The public constructor accepts a list of clusters to become the models |
Uses of Cluster in org.apache.mahout.clustering.canopy |
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Classes in org.apache.mahout.clustering.canopy that implement Cluster | |
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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 |
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Classes in org.apache.mahout.clustering.dirichlet that implement Cluster | |
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class |
DirichletCluster
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Methods in org.apache.mahout.clustering.dirichlet that return Cluster | |
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Cluster |
DirichletCluster.getModel()
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Cluster[] |
DirichletReducer.getNewModels()
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static Cluster |
DirichletCluster.readModel(DataInput in)
Reads a typed Model instance from the input stream |
Methods in org.apache.mahout.clustering.dirichlet with parameters of type Cluster | |
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void |
DirichletCluster.setModel(Cluster model)
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void |
DirichletState.update(Cluster[] newModels)
Update the receiver with the new models |
protected DirichletCluster |
DirichletClusterer.updateCluster(Cluster model,
int k)
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protected void |
DirichletClusterer.updateModels(Cluster[] newModels)
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Constructors in org.apache.mahout.clustering.dirichlet with parameters of type Cluster | |
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DirichletCluster(Cluster model)
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DirichletCluster(Cluster model,
double totalCount)
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Uses of Cluster in org.apache.mahout.clustering.dirichlet.models |
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Classes in org.apache.mahout.clustering.dirichlet.models that implement Cluster | |
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class |
GaussianCluster
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Uses of Cluster in org.apache.mahout.clustering.fuzzykmeans |
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Classes in org.apache.mahout.clustering.fuzzykmeans that implement Cluster | |
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class |
SoftCluster
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Uses of Cluster in org.apache.mahout.clustering.kmeans |
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Classes in org.apache.mahout.clustering.kmeans that implement Cluster | |
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class |
Cluster
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Uses of Cluster in org.apache.mahout.clustering.meanshift |
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Classes in org.apache.mahout.clustering.meanshift that implement Cluster | |
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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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