gov.sandia.cognition.learning.algorithm.nearest

Class KNearestNeighborExhaustive.Learner<InputType,OutputType>

java.lang.Object

gov.sandia.cognition.util.AbstractCloneableSerializable

gov.sandia.cognition.learning.function.distance.DefaultDivergenceFunctionContainer<InputType,InputType>

gov.sandia.cognition.learning.algorithm.nearest.AbstractNearestNeighbor<InputType,OutputType>

gov.sandia.cognition.learning.algorithm.nearest.AbstractKNearestNeighbor<InputType,OutputType>

gov.sandia.cognition.learning.algorithm.nearest.KNearestNeighborExhaustive<InputType,OutputType>

gov.sandia.cognition.learning.algorithm.nearest.KNearestNeighborExhaustive.Learner<InputType,OutputType>

Type Parameters:

InputType - Type of data upon which the KNearestNeighborExhaustive operates, something like Vector, Double, or String

OutputType - Output of the evaluator, like Matrix, Double, String

All Implemented Interfaces:

Evaluator<InputType,OutputType>, BatchLearner<java.util.Collection<? extends InputOutputPair<? extends InputType,OutputType>>,KNearestNeighborExhaustive<InputType,OutputType>>, KNearestNeighbor<InputType,OutputType>, NearestNeighbor<InputType,OutputType>, SupervisedBatchLearner<InputType,OutputType,KNearestNeighborExhaustive<InputType,OutputType>>, DivergenceFunctionContainer<InputType,InputType>, CloneableSerializable, java.io.Serializable, java.lang.Cloneable

Enclosing class:

KNearestNeighborExhaustive<InputType,OutputType>

public static class KNearestNeighborExhaustive.Learner<InputType,OutputType>
extends KNearestNeighborExhaustive<InputType,OutputType>
implements SupervisedBatchLearner<InputType,OutputType,KNearestNeighborExhaustive<InputType,OutputType>>

This is a BatchLearner interface for creating a new KNearestNeighborExhaustive from a given dataset, simply a pass-through to the constructor of KNearestNeighborExhaustive

See Also:

Serialized Form

Nested Class Summary

Nested classes/interfaces inherited from class gov.sandia.cognition.learning.algorithm.nearest.KNearestNeighborExhaustive

KNearestNeighborExhaustive.Learner<InputType,OutputType>, KNearestNeighborExhaustive.Neighbor

Field Summary

Fields inherited from class gov.sandia.cognition.learning.function.distance.DefaultDivergenceFunctionContainer

divergenceFunction

Fields inherited from interface gov.sandia.cognition.learning.algorithm.nearest.KNearestNeighbor

DEFAULT_K

Constructor Summary

Constructors

Constructor and Description
Learner() Default constructor.
Learner(int k, DivergenceFunction<? super InputType,? super InputType> divergenceFunction, Summarizer<? super OutputType,OutputType> averager) Creates a new instance of Learner

Method Summary

Modifier and Type	Method and Description
KNearestNeighborExhaustive<InputType,OutputType>	learn(java.util.Collection<? extends InputOutputPair<? extends InputType,OutputType>> data) Creates a new KNearestNeighborExhaustive from a Collection of InputType.

Methods inherited from class gov.sandia.cognition.learning.algorithm.nearest.KNearestNeighborExhaustive

clone, computeNeighborhood, getData, setData

Methods inherited from class gov.sandia.cognition.learning.algorithm.nearest.AbstractKNearestNeighbor

evaluate, getAverager, getK, setAverager, setK

Methods inherited from class gov.sandia.cognition.learning.algorithm.nearest.AbstractNearestNeighbor

add

Methods inherited from class gov.sandia.cognition.learning.function.distance.DefaultDivergenceFunctionContainer

getDivergenceFunction, setDivergenceFunction

Methods inherited from class java.lang.Object

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

Methods inherited from interface gov.sandia.cognition.util.CloneableSerializable

clone

Methods inherited from interface gov.sandia.cognition.learning.algorithm.nearest.NearestNeighbor

add, getDivergenceFunction

Constructor Detail

Learner

public Learner()

Default constructor.

Learner

public Learner(int k,
               DivergenceFunction<? super InputType,? super InputType> divergenceFunction,
               Summarizer<? super OutputType,OutputType> averager)

Creates a new instance of Learner

Parameters:

k - Number of neighbors to consider, must be greater than zero

divergenceFunction - Divergence function that determines how "far" two objects are apart, where lower values indicate two objects are more similar

averager - Creates a single object from a collection of data

Method Detail

learn

public KNearestNeighborExhaustive<InputType,OutputType> learn(java.util.Collection<? extends InputOutputPair<? extends InputType,OutputType>> data)

Creates a new KNearestNeighborExhaustive from a Collection of InputType. This is simply a pass-through to the constructor, and there is no computation time associated with this function call.

Specified by:

learn in interface BatchLearner<java.util.Collection<? extends InputOutputPair<? extends InputType,OutputType>>,KNearestNeighborExhaustive<InputType,OutputType>>

Parameters:

data - Dataset from which to create a new KNearestNeighborExhaustive

Returns:

KNearestNeighborExhaustive based on the given dataset.