## Uses of Classde.aitools.aq.algebra.vector.Vector

Uses of Vector in de.aitools.aq.algebra.vector

Methods in de.aitools.aq.algebra.vector that return Vector
`static Vector` `Vector.centroid(java.lang.Iterable<Vector> vectors)`

`static Vector` ```Vector.multiply(Vector vector, double[] values)```

`static Vector` ```Vector.multiply(Vector v1, Vector v2)```

Methods in de.aitools.aq.algebra.vector with parameters of type Vector
` void` `Vector.add(Vector vector)`

` double` `Vector.dot(Vector vector)`

` void` `Vector.multiply(Vector vector)`

`static Vector` ```Vector.multiply(Vector vector, double[] values)```

`static Vector` ```Vector.multiply(Vector v1, Vector v2)```

`static int[]` `VectorSort.sortedIndices(Vector input)`
Return the indices of the input vector, sorted in descending order.

Method parameters in de.aitools.aq.algebra.vector with type arguments of type Vector
`static Vector` `Vector.centroid(java.lang.Iterable<Vector> vectors)`

Constructors in de.aitools.aq.algebra.vector with parameters of type Vector
`Vector(Vector vector)`

```VectorSort(Vector nodeValues, boolean copyVector)```
Create a new `VectorSort`.
```VectorSort(Vector nodeValues, boolean copyVector, int numNodes)```
Create a new `VectorSort`.

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

Fields in de.aitools.aq.algebra.vector.functions with type parameters of type Vector
` Proximity<Vector>` `TestVectorProximityCommon.proximity`

Methods in de.aitools.aq.algebra.vector.functions with parameters of type Vector
` double` ```ManhattanDistance.computeDistance(Vector v1, Vector v2)```

` double` ```EuclideanDistance.computeDistance(Vector v1, Vector v2)```

` double` ```ManhattanDistance.computeNormalizedProximity(Vector v1, Vector v2)```

` double` ```CosineSimilarity.computeNormalizedProximity(Vector v1, Vector v2)```

` double` ```DotProduct.computeNormalizedProximity(Vector v1, Vector v2)```

` double` ```EuclideanDistance.computeNormalizedProximity(Vector v1, Vector v2)```

` double` ```ManhattanDistance.computeProximity(Vector v1, Vector v2)```

` double` ```CosineSimilarity.computeProximity(Vector v1, Vector v2)```

` double` ```DotProduct.computeProximity(Vector v1, Vector v2)```

` double` ```EuclideanDistance.computeProximity(Vector v1, Vector v2)```

` double` ```CosineSimilarity.computeSimilarity(Vector v1, Vector v2)```

` double` ```EuclideanDistance.computeSquaredDistance(Vector v1, Vector v2)```

Constructor parameters in de.aitools.aq.algebra.vector.functions with type arguments of type Vector
`TestVectorProximityCommon(Proximity<Vector> proximityMeasure)`

Uses of Vector in de.aitools.aq.graph

Methods in de.aitools.aq.graph that return Vector
` Vector` `UndirectedGraph.getAdjacentNodes(int node)`

` Vector` `Graph.getAdjacentNodes(int nodeId)`

Constructors in de.aitools.aq.graph with parameters of type Vector
`UndirectedGraph(Vector[] adjacencyMatrix)`

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

Methods in de.aitools.aq.graph.util with parameters of type Vector
` void` ```Sparsification.init(Vector[] data, Proximity<Vector> proximity)```

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

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

Method parameters in de.aitools.aq.graph.util with type arguments of type Vector
` 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 Vector in de.aitools.aq.graph.weighted.util

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

Method parameters in de.aitools.aq.graph.weighted.util with type arguments of type Vector
```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 Vector in de.aitools.dm.clustering

Methods in de.aitools.dm.clustering that return Vector
`static Vector[]` `ClusteringIO.read(java.io.InputStream in)`

Methods in de.aitools.dm.clustering with parameters of type Vector
` int[]` `Clusterer.cluster(Vector[] data)`

` int[][]` `SoftClusterer.clusterSoft(Vector[] data)`

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

Fields in de.aitools.dm.clustering.algorithms declared as Vector
`static Vector[]` `HACTests.data`
Testdata to use.
`static Vector[]` `TestDBScan.DATA`

Methods in de.aitools.dm.clustering.algorithms that return Vector
` Vector[]` `KMeans.getCentroids()`
Returs the centroids of the clusters that were found during the last clustering process.

Methods in de.aitools.dm.clustering.algorithms that return types with arguments of type Vector
` Proximity<Vector>` `KMeans.getProximity()`
Get the proximity.
` Proximity<Vector>` `KNNHAC.getProximityMeasure()`

Methods in de.aitools.dm.clustering.algorithms with parameters of type Vector
` int[]` `SLink.cluster(Vector[] data)`
This method is used for clustering via the TIRA Framework.
` int[]` `DBScan.cluster(Vector[] data)`

` int[]` `DBScan.DBScanConfiguration.cluster(Vector[] data)`
TODO
` int[]` `DBScan.DBScanAllParameters.cluster(Vector[] data)`

` int[]` `DBScan.DBScanSearchProximity.cluster(Vector[] data)`

` int[]` `AGraphClusterer.cluster(Vector[] data)`

` int[]` `KNNHAC.cluster(Vector[] data)`
This method is used for clustering via the TIRA Framework.
` int[]` `KMeans.cluster(Vector[] data)`

`abstract  int[]` `AClusterer.cluster(Vector[] data)`

` int[]` `HighRecallClusterer.cluster(Vector[] data)`

` int[]` ```SLink.cluster(Vector[] data, double threshold)```
Cluster given data hierarchically until the proximities between all clusters is less or equal to threshold.
` int[]` ```KNNHAC.cluster(Vector[] data, double threshold)```
Cluster given data hierarchically until the proximities between all clusters is less or equal to threshold.
` int[]` ```SLink.cluster(Vector[] data, int numClusters)```
Cluster given data hierarchically until only numClusters are left.
` int[]` ```DBScan.cluster(Vector[] data, int coreMinNeighbors)```
TODO
` int[]` ```KNNHAC.cluster(Vector[] data, int numClusters)```
Cluster given data hierarchically until only numClusters are left.
` int[]` ```DBScan.cluster(Vector[] data, int coreMinNeighbors, DBScan.DBScanGraphKneeDetector neighborhoodProximityDetector)```
TODO
` int[]` ```DBScan.cluster(Vector[] data, int coreMinNeighbors, double neighborhoodProximity)```
TODO
` Dendrogram<DoubleMerge>` `SLink.clusterDendrogram(Vector[] data)`
Cluster given data hierarchically.
` Dendrogram<DoubleMerge>` `KNNHAC.clusterDendrogram(Vector[] data)`
Cluster given data hierarchically.
` int[][]` `AClusterer.clusterSoft(Vector[] data)`

`abstract  int[][]` `ASoftClusterer.clusterSoft(Vector[] data)`

`static Graph` ```AGraphClusterer.createGraph(Vector[] data, Proximity<Vector> proximity, double threshold)```

`static int` `ASoftClusterer.getBiggestRange(Vector[] data)`

Method parameters in de.aitools.dm.clustering.algorithms with type arguments of type Vector
`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.

Constructor parameters in de.aitools.dm.clustering.algorithms with type arguments of type Vector
```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 Vector in de.aitools.dm.clustering.algorithms.dbscan

Methods in de.aitools.dm.clustering.algorithms.dbscan with parameters of type Vector
`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)```

Method parameters in de.aitools.dm.clustering.algorithms.dbscan with type arguments of type Vector
`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)```

Uses of Vector in de.aitools.dm.clustering.validation

Methods in de.aitools.dm.clustering.validation with parameters of type Vector
` java.util.Map<java.lang.String,java.lang.Double>` ```InternalClusterValidator.validate(Distance<Vector> dm, Vector[] points, int[] clustering)```

Method parameters in de.aitools.dm.clustering.validation with type arguments of type Vector
` java.util.Map<java.lang.String,java.lang.Double>` ```InternalClusterValidator.validate(Distance<Vector> dm, Vector[] points, int[] clustering)```

Constructors in de.aitools.dm.clustering.validation.internal with parameters of type Vector
```DaviesBouldinIndex(Distance<Vector> dm, Vector[] points, int[] clusterResult)```

```DunnIndex(Distance<Vector> dm, Vector[] points, int[] clusterResult)```

```SilhouetteCoefficient(Distance<Vector> dm, Vector[] points, int[] clusterResult)```

Constructor parameters in de.aitools.dm.clustering.validation.internal with type arguments of type Vector
```DaviesBouldinIndex(Distance<Vector> dm, Vector[] points, int[] clusterResult)```

```DunnIndex(Distance<Vector> dm, Vector[] points, int[] clusterResult)```

```SilhouetteCoefficient(Distance<Vector> dm, Vector[] points, int[] clusterResult)```

Uses of Vector in de.aitools.dm.clusterlabeling.algorithms

Methods in de.aitools.dm.clusterlabeling.algorithms with parameters of type Vector
` int[]` `TopicIdentifier.cluster(Vector[] data)`

` int[][]` `ACarrot2ClusterLabeler.clusterSoft(Vector[] data)`

Uses of Vector in de.aitools.ir.fingerprinting.hashfunction

Methods in de.aitools.ir.fingerprinting.hashfunction with parameters of type Vector
` java.math.BigInteger` `FuzzyFingerprintingEncoding.hash(Vector document)`

` java.math.BigInteger` `LocalitySensitiveEncoding.hash(Vector document)`

Uses of Vector in de.aitools.ir.fingerprinting.representer

Methods in de.aitools.ir.fingerprinting.representer that return Vector
` Vector` `PrefixClassFunction.represent(java.lang.String document)`
Returns the dimensional reduced deviation vector of the document's prefix classes.
` Vector` `RandomProjectionFunction.represent(java.lang.String text)`

Methods in de.aitools.ir.fingerprinting.representer that return types with arguments of type Vector
` java.util.List<Vector>` `RandomProjectionFunction.createRandomVectors(int number)`

Method parameters in de.aitools.ir.fingerprinting.representer with type arguments of type Vector
` void` `RandomProjectionFunction.setRandomVectors(java.util.List<Vector> randomVectors)`

Methods in de.aitools.ir.retrievalmodels.relevance.algebraic with parameters of type Vector
` double` ```CosineSimilarity.compute(Vector v1, Vector v2)```
Computes and returns the cosine similarity between two vectors.
` double` ```DotProductSimilarity.compute(Vector v1, Vector v2)```

Methods in de.aitools.ir.retrievalmodels.relevance.probabilistic with parameters of type Vector
` double` ```JensenShannonDivergence.compute(Vector p1, Vector p2)```

` double` ```KullbackLeiblerDivergence.compute(Vector p1, Vector p2)```

Uses of Vector in de.aitools.ir.retrievalmodels.representer

Methods in de.aitools.ir.retrievalmodels.representer that return Vector
` Vector` `InverseDocumentFrequency.represent(java.lang.Iterable<java.lang.String> texts)`

` Vector` `LatentSemanticIndexing.represent(java.lang.String text)`

` Vector` `TermFrequency.represent(java.lang.String text)`

` Vector` `DivergenceFromRandomness.represent(java.lang.String text)`

` Vector` `SerializableTermFrequency.represent(java.lang.String text)`

` Vector` `TFIDF.represent(java.lang.String text)`

` Vector` `TFPDF.represent(java.lang.String text)`

` Vector` `OkapiBM25.represent(java.lang.String text)`

` Vector` `OkapiBM25.RepresentationState.represent(java.lang.String text)`

` Vector` `OkapiBM25.DocumentState.represent(java.lang.String text)`

` Vector` `OkapiBM25.QueryState.represent(java.lang.String text)`

Methods in de.aitools.ir.retrievalmodels.representer that return types with arguments of type Vector
` Representer<java.lang.String,Vector>` `LatentSemanticIndexing.getRepresenter()`

Constructor parameters in de.aitools.ir.retrievalmodels.representer with type arguments of type Vector
`LatentSemanticIndexing(Representer<java.lang.String,Vector> representer)`

Methods in de.aitools.ir.retrievalmodels.retrievalmodel that return Vector
` Vector` `ExplicitSemanticAnalysis.represent(java.lang.String text)`

` Vector` `VectorSpaceModel.represent(java.lang.String text)`

Constructor parameters in de.aitools.ir.retrievalmodels.retrievalmodel with type arguments of type Vector
```VectorSpaceModel(Representer<java.lang.String,Vector> representer, RelevanceFunction<Vector,Vector> rho)```

```VectorSpaceModel(Representer<java.lang.String,Vector> representer, RelevanceFunction<Vector,Vector> rho)```

```VectorSpaceModel(Representer<java.lang.String,Vector> representer, RelevanceFunction<Vector,Vector> rho)```