Package | Description |
---|---|
org.hipparchus.clustering |
Clustering algorithms.
|
org.hipparchus.clustering.evaluation |
Cluster evaluation methods.
|
Modifier and Type | Class and Description |
---|---|
class |
CentroidCluster<T extends Clusterable>
A Cluster used by centroid-based clustering algorithms.
|
class |
Cluster<T extends Clusterable>
Cluster holding a set of
Clusterable points. |
class |
Clusterer<T extends Clusterable>
Base class for clustering algorithms.
|
class |
DBSCANClusterer<T extends Clusterable>
DBSCAN (density-based spatial clustering of applications with noise) algorithm.
|
class |
FuzzyKMeansClusterer<T extends Clusterable>
Fuzzy K-Means clustering algorithm.
|
class |
KMeansPlusPlusClusterer<T extends Clusterable>
Clustering algorithm based on David Arthur and Sergei Vassilvitski k-means++ algorithm.
|
class |
MultiKMeansPlusPlusClusterer<T extends Clusterable>
A wrapper around a k-means++ clustering algorithm which performs multiple trials
and returns the best solution.
|
Modifier and Type | Class and Description |
---|---|
class |
DoublePoint
A simple implementation of
Clusterable for points with double coordinates. |
Modifier and Type | Method and Description |
---|---|
Clusterable |
CentroidCluster.getCenter()
Get the point chosen to be the center of this cluster.
|
Modifier and Type | Method and Description |
---|---|
protected double |
Clusterer.distance(Clusterable p1,
Clusterable p2)
Calculates the distance between two
Clusterable instances
with the configured DistanceMeasure . |
Constructor and Description |
---|
CentroidCluster(Clusterable center)
Build a cluster centered at a specified point.
|
Modifier and Type | Class and Description |
---|---|
class |
ClusterEvaluator<T extends Clusterable>
Base class for cluster evaluation methods.
|
class |
SumOfClusterVariances<T extends Clusterable>
Computes the sum of intra-cluster distance variances according to the formula:
\] score = \sum\limits_{i=1}^n \sigma_i^2 \]
where n is the number of clusters and \( \sigma_i^2 \) is the variance of
intra-cluster distances of cluster \( c_i \).
|
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 |
---|---|
protected double |
ClusterEvaluator.distance(Clusterable p1,
Clusterable p2)
Calculates the distance between two
Clusterable instances
with the configured DistanceMeasure . |
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