Uses of Interface
de.aitools.aq.algebra.vector.functions.Proximity

Packages that use Proximity

de.aitools.aq.algebra.vector.functions
de.aitools.aq.graph.util
de.aitools.aq.graph.weighted.util
de.aitools.dm.clustering.algorithms
de.aitools.dm.clustering.algorithms.dbscan

Uses of Proximity in de.aitools.aq.algebra.vector.functions

Subinterfaces of Proximity in de.aitools.aq.algebra.vector.functions

interface	Distance<T> A measure for computing how far away two objects are from each other. The Proximity of a distance measure is most likely the negative distance.
interface	Similarity<T> A measure for computing how similar two objects are.

Classes in de.aitools.aq.algebra.vector.functions that implement Proximity

class	CosineSimilarity A Similarity measure for Vectors. The Cosine Similarity of two vectors is defined as the cosine of the angle between them. It is calculated as the dot product of the both vectors divided by the multiplied euclidean norms of both. The resulting similarity of a vector a and a vector b is between -1 (if a equals -b * k) and 1 (if a equals b * k), with k being a positive rational number (and thus not zero).
class	DotProduct The Dot Product of two vectors is defined as the sum of the pairwise products of the coordinate values of the vectors. This is not a real proximity measure.
class	EuclideanDistance A Distance measure for Vectors. The Euclidean Distance of two points is defined as the length of the segment between them.
class	ManhattanDistance A Distance measure for Vectors. The Manhattan Distance of two points is defined as the sum of the lengths of the projections of the segment between them onto the coordinate system axis.

Fields in de.aitools.aq.algebra.vector.functions declared as Proximity

Proximity<Vector>

TestVectorProximityCommon.proximity

Constructors in de.aitools.aq.algebra.vector.functions with parameters of type Proximity

TestVectorProximityCommon(Proximity<Vector> proximityMeasure)

Uses of Proximity in de.aitools.aq.graph.util

Methods in de.aitools.aq.graph.util with parameters of type Proximity

void	Sparsification.init(Vector[] data, Proximity<Vector> proximity)
void	Threshold.init(Vector[] data, Proximity<Vector> proximity)
void	NoSparsification.init(Vector[] data, Proximity<Vector> proximity)

Uses of Proximity in de.aitools.aq.graph.weighted.util

Methods in de.aitools.aq.graph.weighted.util with parameters of type Proximity

static <V> UndirectedMutableGraph<V>	KNNGraph.createUndirectedKNNGraph(Vector[] data, V[] vertices, java.util.Comparator<V> vertexComparator, Proximity<Vector> proximity, int k) Deprecated. Create an undirected K-Nearest-Neighbor-Graph.
static <V> UndirectedMutableGraph<V>	KNNGraph.createUndirectedKNNGraph(Vector[] data, V[] vertices, java.util.Comparator<V> vertexComparator, Proximity<Vector> proximity, int k, double noEdgeWeight) Deprecated. Create an undirected K-Nearest-Neighbor-Graph.
static UndirectedMutableIntGraph	KNNGraph.createUndirectedKNNIntGraph(Vector[] data, Proximity<Vector> proximity, int k) Deprecated. Create an undirected K-Nearest-Neighbor-Graph.
static UndirectedMutableIntGraph	KNNGraph.createUndirectedKNNIntGraph(Vector[] data, Proximity<Vector> proximity, int k, double noEdgeWeight) Deprecated. Create an undirected K-Nearest-Neighbor-Graph.

Uses of Proximity in de.aitools.dm.clustering.algorithms

Methods in de.aitools.dm.clustering.algorithms that return Proximity

Proximity<Vector>	KMeans.getProximity() Get the proximity.
Proximity<Vector>	KNNHAC.getProximityMeasure()

Methods in de.aitools.dm.clustering.algorithms with parameters of type Proximity

static Graph	AGraphClusterer.createGraph(Vector[] data, Proximity<Vector> proximity, double threshold)
void	AGraphClusterer.setProximity(Proximity<Vector> proximityMeasure)
void	SLink.setProximityMeasure(Proximity<Vector> proximityMeasure) Sets the proximity measure to be used for the clustering steps.
void	DBScan.setProximityMeasure(Proximity<Vector> proximityMeasure) Sets the proximity measure to be used for clustering.
void	KNNHAC.setProximityMeasure(Proximity<Vector> proximityMeasure) Sets the proximity measure to be used for the clustering steps.
void	KMeans.setProximityMeasure(Proximity<Vector> proximityMeasure) Sets a proximity measure.

Constructors in de.aitools.dm.clustering.algorithms with parameters of type Proximity

AGraphClusterer(Proximity<Vector> proximityMeasure, Sparsification sparsificationMethod)

DBScan(Proximity<Vector> proximityMeasure)
TODO

KMeans(int k, Proximity<Vector> proximityMeasure, boolean updateIncremental)
The constructor to use in most cases.
The default seed for randomization is used.

KMeans(int k, Proximity<Vector> proximityMeasure, boolean updateIncremental, long seed)
If one does not want to try out another seed value, use the constructor with the default seed value (without the randomSeed parameter) instead.

KNNHAC(HACClusterMethod clusterMethod, Proximity<Vector> proximityMeasure)
Create a new K-Nearest-Neighbor-Hierarchical-Agglomerative-Clusterer (KNNHAC) using the default value for the number of neighbors (see KNNHAC.setNumberOfNeighbors(int)).

KNNHAC(HACClusterMethod clusterMethod, Proximity<Vector> proximityMeasure, int numNeighbors)
Create a new K-Nearest-Neighbor-Hierarchical-Agglomerative-Clusterer (KNNHAC).

MajorClust(Proximity<Vector> proximityMeasure, Sparsification sparsificationMethod, double minimumProximity)
Creates a new MajorClust-Clusterer using random ordering of instances.

MajorClust(Proximity<Vector> proximityMeasure, Sparsification sparsificationMethod, long randomNumberSeed, double minimumProximity)
Creates a new MajorClust-Clusterer.

SLink(Proximity<Vector> proximityMeasure)
Create a new Single Link Clusterer.
This allows only to use SLink.cluster(Vector[], int), SLink.cluster(Vector[], double) and SLink.clusterDendrogram(Vector[]).

Uses of Proximity in de.aitools.dm.clustering.algorithms.dbscan

Methods in de.aitools.dm.clustering.algorithms.dbscan with parameters of type Proximity

static void	ProximitySorter.gnuplot(Vector[] data, Proximity<Vector> proximityMeasure, int minNeighbor, int stepWidth, int numSteps, java.lang.String filepath)
static UndirectedMutableGraph<Point>	ProximitySorter.neighborGraph(Vector[] data, Proximity<Vector> proximityMeasure, int numNeighbors)