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