## Uses of Interfacede.aitools.aq.algebra.vector.functions.Proximity

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 `Vector`s.
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 `Vector`s.
The Euclidean Distance of two points is defined as the length of the segment between them.
` class` `ManhattanDistance`
A `Distance` measure for `Vector`s.
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[])`.

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)```