Package | Description |
---|---|
org.apache.commons.math3.ml.clustering |
Clustering algorithms.
|
org.apache.commons.math3.ml.clustering.evaluation |
Cluster evaluation methods.
|
Modifier and Type | Class and Description |
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class |
CentroidCluster<T extends Clusterable>
A Cluster used by centroid-based clustering algorithms.
|
Modifier and Type | Method and Description |
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private Cluster<T> |
DBSCANClusterer.expandCluster(Cluster<T> cluster,
T point,
java.util.List<T> neighbors,
java.util.Collection<T> points,
java.util.Map<Clusterable,DBSCANClusterer.PointStatus> visited)
Expands the cluster to include density-reachable items.
|
Modifier and Type | Method and Description |
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java.util.List<Cluster<T>> |
DBSCANClusterer.cluster(java.util.Collection<T> points)
Performs DBSCAN cluster analysis.
|
abstract java.util.List<? extends Cluster<T>> |
Clusterer.cluster(java.util.Collection<T> points)
Perform a cluster analysis on the given set of
Clusterable instances. |
Modifier and Type | Method and Description |
---|---|
private Cluster<T> |
DBSCANClusterer.expandCluster(Cluster<T> cluster,
T point,
java.util.List<T> neighbors,
java.util.Collection<T> points,
java.util.Map<Clusterable,DBSCANClusterer.PointStatus> visited)
Expands the cluster to include density-reachable items.
|
Modifier and Type | Method and Description |
---|---|
private T |
KMeansPlusPlusClusterer.getPointFromLargestNumberCluster(java.util.Collection<? extends Cluster<T>> clusters)
Get a random point from the
Cluster with the largest number of points |
Modifier and Type | Method and Description |
---|---|
protected Clusterable |
ClusterEvaluator.centroidOf(Cluster<T> cluster)
Computes the centroid for a cluster.
|
Modifier and Type | Method and Description |
---|---|
abstract double |
ClusterEvaluator.score(java.util.List<? extends Cluster<T>> clusters)
Computes the evaluation score for the given list of clusters.
|
double |
SumOfClusterVariances.score(java.util.List<? extends Cluster<T>> clusters) |