org.deeplearning4j.clustering.vptree

Class VPTree

java.lang.Object

org.deeplearning4j.clustering.vptree.VPTree

All Implemented Interfaces:

Serializable

public class VPTree
extends Object
implements Serializable

Vantage point tree implementation

Author:

Adam Gibson, raver119@gmail.com

See Also:

Serialized Form

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
protected class	VPTree.HeapObjectComparator
static class	VPTree.Node
protected class	VPTree.NodeBuilder

Field Summary

Fields

Modifier and Type	Field and Description
static String	EUCLIDEAN

Constructor Summary

Constructors

Modifier	Constructor and Description
protected	VPTree()
	VPTree(INDArray items)
	VPTree(INDArray points, boolean invert)
	VPTree(INDArray points, boolean invert, int workers)
	VPTree(INDArray items, String similarityFunction)
	VPTree(INDArray items, String similarityFunction, boolean invert)
	VPTree(INDArray items, String similarityFunction, int workers, boolean invert)
	VPTree(List<DataPoint> items)
	VPTree(List<DataPoint> items, String similarityFunction)
	VPTree(List<DataPoint> items, String similarityFunction, int workers, boolean invert)

Method Summary

Modifier and Type	Method and Description
static INDArray	buildFromData(List<DataPoint> data) Create an ndarray from the datapoints
void	calcDistancesRelativeTo(INDArray basePoint, INDArray distancesArr)
void	calcDistancesRelativeTo(INDArray items, INDArray basePoint, INDArray distancesArr)
double	distance(INDArray arr1, INDArray arr2) Euclidean distance
void	search(@NonNull INDArray target, int k, List<DataPoint> results, List<Double> distances)
void	search(@NonNull INDArray target, int k, List<DataPoint> results, List<Double> distances, boolean filterEqual)
void	search(@NonNull INDArray target, int k, List<DataPoint> results, List<Double> distances, boolean filterEqual, boolean dropEdge)
void	search(VPTree.Node node, INDArray target, int k, PriorityQueue<HeapObject> pq, double cTau)

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Field Detail

EUCLIDEAN

public static final String EUCLIDEAN

See Also:

Constant Field Values

Constructor Detail

VPTree

protected VPTree()

VPTree

public VPTree(INDArray points,
              boolean invert)

Parameters:

points -

invert -

VPTree

public VPTree(INDArray points,
              boolean invert,
              int workers)

Parameters:

points -

invert -

workers - number of parallel workers for tree building (increases memory requirements!)

VPTree

public VPTree(INDArray items,
              String similarityFunction,
              boolean invert)

Parameters:

items - the items to use

similarityFunction - the similarity function to use

invert - whether to invert the distance (similarity functions have different min/max objectives)

VPTree

public VPTree(List<DataPoint> items,
              String similarityFunction,
              int workers,
              boolean invert)

Parameters:

items - the items to use

similarityFunction - the similarity function to use

workers - number of parallel workers for tree building (increases memory requirements!)

invert - whether to invert the metric (different optimization objective)

VPTree

public VPTree(INDArray items,
              String similarityFunction)

Parameters:

items -

similarityFunction -

VPTree

public VPTree(INDArray items,
              String similarityFunction,
              int workers,
              boolean invert)

Parameters:

items -

similarityFunction -

workers - number of parallel workers for tree building (increases memory requirements!)

invert -

VPTree

public VPTree(List<DataPoint> items,
              String similarityFunction)

Parameters:

items -

similarityFunction -

VPTree

public VPTree(INDArray items)

Parameters:

items -

VPTree

public VPTree(List<DataPoint> items)

Parameters:

items -

Method Detail

buildFromData

public static INDArray buildFromData(List<DataPoint> data)

Create an ndarray from the datapoints

Parameters:

data -

Returns:

calcDistancesRelativeTo

public void calcDistancesRelativeTo(INDArray items,
                                    INDArray basePoint,
                                    INDArray distancesArr)

Parameters:

basePoint -

distancesArr -

calcDistancesRelativeTo

public void calcDistancesRelativeTo(INDArray basePoint,
                                    INDArray distancesArr)

distance

public double distance(INDArray arr1,
                       INDArray arr2)

Euclidean distance

Returns:

the distance between the two points

search

public void search(@NonNull
                   @NonNull INDArray target,
                   int k,
                   List<DataPoint> results,
                   List<Double> distances)

search

public void search(@NonNull
                   @NonNull INDArray target,
                   int k,
                   List<DataPoint> results,
                   List<Double> distances,
                   boolean filterEqual)

search

public void search(@NonNull
                   @NonNull INDArray target,
                   int k,
                   List<DataPoint> results,
                   List<Double> distances,
                   boolean filterEqual,
                   boolean dropEdge)

Parameters:

target -

k -

results -

distances -

search

public void search(VPTree.Node node,
                   INDArray target,
                   int k,
                   PriorityQueue<HeapObject> pq,
                   double cTau)

Parameters:

node -

target -

k -

pq -