- CanberraDistance - Class in org.hipparchus.clustering.distance
-
Calculates the Canberra distance between two points.
- CanberraDistance() - Constructor for class org.hipparchus.clustering.distance.CanberraDistance
-
- CentroidCluster<T extends Clusterable> - Class in org.hipparchus.clustering
-
A Cluster used by centroid-based clustering algorithms.
- CentroidCluster(Clusterable) - Constructor for class org.hipparchus.clustering.CentroidCluster
-
Build a cluster centered at a specified point.
- centroidOf(Cluster<T>) - Method in class org.hipparchus.clustering.evaluation.ClusterEvaluator
-
Computes the centroid for a cluster.
- ChebyshevDistance - Class in org.hipparchus.clustering.distance
-
Calculates the L∞ (max of abs) distance between two points.
- ChebyshevDistance() - Constructor for class org.hipparchus.clustering.distance.ChebyshevDistance
-
- Cluster<T extends Clusterable> - Class in org.hipparchus.clustering
-
- Cluster() - Constructor for class org.hipparchus.clustering.Cluster
-
Build a cluster centered at a specified point.
- cluster(Collection<T>) - Method in class org.hipparchus.clustering.Clusterer
-
Perform a cluster analysis on the given set of
Clusterable
instances.
- cluster(Collection<T>) - Method in class org.hipparchus.clustering.DBSCANClusterer
-
Performs DBSCAN cluster analysis.
- cluster(Collection<T>) - Method in class org.hipparchus.clustering.FuzzyKMeansClusterer
-
Performs Fuzzy K-Means cluster analysis.
- cluster(Collection<T>) - Method in class org.hipparchus.clustering.KMeansPlusPlusClusterer
-
Runs the K-means++ clustering algorithm.
- cluster(Collection<T>) - Method in class org.hipparchus.clustering.MultiKMeansPlusPlusClusterer
-
Runs the K-means++ clustering algorithm.
- Clusterable - Interface in org.hipparchus.clustering
-
Interface for n-dimensional points that can be clustered together.
- Clusterer<T extends Clusterable> - Class in org.hipparchus.clustering
-
Base class for clustering algorithms.
- Clusterer(DistanceMeasure) - Constructor for class org.hipparchus.clustering.Clusterer
-
- ClusterEvaluator<T extends Clusterable> - Class in org.hipparchus.clustering.evaluation
-
Base class for cluster evaluation methods.
- ClusterEvaluator() - Constructor for class org.hipparchus.clustering.evaluation.ClusterEvaluator
-
- ClusterEvaluator(DistanceMeasure) - Constructor for class org.hipparchus.clustering.evaluation.ClusterEvaluator
-
Creates a new cluster evaluator with the given distance measure.
- compute(double[], double[]) - Method in class org.hipparchus.clustering.distance.CanberraDistance
-
Compute the distance between two n-dimensional vectors.
- compute(double[], double[]) - Method in class org.hipparchus.clustering.distance.ChebyshevDistance
-
Compute the distance between two n-dimensional vectors.
- compute(double[], double[]) - Method in interface org.hipparchus.clustering.distance.DistanceMeasure
-
Compute the distance between two n-dimensional vectors.
- compute(double[], double[]) - Method in class org.hipparchus.clustering.distance.EarthMoversDistance
-
Compute the distance between two n-dimensional vectors.
- compute(double[], double[]) - Method in class org.hipparchus.clustering.distance.EuclideanDistance
-
Compute the distance between two n-dimensional vectors.
- compute(double[], double[]) - Method in class org.hipparchus.clustering.distance.ManhattanDistance
-
Compute the distance between two n-dimensional vectors.
- getCenter() - Method in class org.hipparchus.clustering.CentroidCluster
-
Get the point chosen to be the center of this cluster.
- getClusterer() - Method in class org.hipparchus.clustering.MultiKMeansPlusPlusClusterer
-
Returns the embedded k-means clusterer used by this instance.
- getClusterEvaluator() - Method in class org.hipparchus.clustering.MultiKMeansPlusPlusClusterer
-
- getClusters() - Method in class org.hipparchus.clustering.FuzzyKMeansClusterer
-
- getDataPoints() - Method in class org.hipparchus.clustering.FuzzyKMeansClusterer
-
- getDistanceMeasure() - Method in class org.hipparchus.clustering.Clusterer
-
- getEmptyClusterStrategy() - Method in class org.hipparchus.clustering.KMeansPlusPlusClusterer
-
- getEps() - Method in class org.hipparchus.clustering.DBSCANClusterer
-
Returns the maximum radius of the neighborhood to be considered.
- getEpsilon() - Method in class org.hipparchus.clustering.FuzzyKMeansClusterer
-
Returns the convergence criteria used by this instance.
- getFuzziness() - Method in class org.hipparchus.clustering.FuzzyKMeansClusterer
-
Returns the fuzziness factor used by this instance.
- getK() - Method in class org.hipparchus.clustering.FuzzyKMeansClusterer
-
Return the number of clusters this instance will use.
- getK() - Method in class org.hipparchus.clustering.KMeansPlusPlusClusterer
-
Return the number of clusters this instance will use.
- getLocalizedString(Locale) - Method in enum org.hipparchus.clustering.LocalizedClusteringFormats
- getMaxIterations() - Method in class org.hipparchus.clustering.FuzzyKMeansClusterer
-
Returns the maximum number of iterations this instance will use.
- getMaxIterations() - Method in class org.hipparchus.clustering.KMeansPlusPlusClusterer
-
Returns the maximum number of iterations this instance will use.
- getMembershipMatrix() - Method in class org.hipparchus.clustering.FuzzyKMeansClusterer
-
Returns the nxk
membership matrix, where n
is the number
of data points and k
the number of clusters.
- getMinPts() - Method in class org.hipparchus.clustering.DBSCANClusterer
-
Returns the minimum number of points needed for a cluster.
- getNumTrials() - Method in class org.hipparchus.clustering.MultiKMeansPlusPlusClusterer
-
Returns the number of trials this instance will do.
- getObjectiveFunctionValue() - Method in class org.hipparchus.clustering.FuzzyKMeansClusterer
-
Get the value of the objective function.
- getPoint() - Method in interface org.hipparchus.clustering.Clusterable
-
Gets the n-dimensional point.
- getPoint() - Method in class org.hipparchus.clustering.DoublePoint
-
Gets the n-dimensional point.
- getPoints() - Method in class org.hipparchus.clustering.Cluster
-
Get the points contained in the cluster.
- getRandomGenerator() - Method in class org.hipparchus.clustering.FuzzyKMeansClusterer
-
Returns the random generator this instance will use.
- getRandomGenerator() - Method in class org.hipparchus.clustering.KMeansPlusPlusClusterer
-
Returns the random generator this instance will use.
- getSourceString() - Method in enum org.hipparchus.clustering.LocalizedClusteringFormats