InputType
- The input type for nearest neighbor.OutputType
- The output type for nearest neighbor.public static class NearestNeighborExhaustive.Learner<InputType,OutputType> extends DefaultDivergenceFunctionContainer<InputType,InputType> implements SupervisedBatchLearner<InputType,OutputType,NearestNeighborExhaustive<InputType,OutputType>>
NearestNeighborExhaustive.Learner
class implements a batch learner for
the NearestNeighborExhaustive
class.divergenceFunction
Constructor and Description |
---|
Learner()
Creates a new instance of
NearestNeighborExhaustive.Learner . |
Learner(DivergenceFunction<? super InputType,? super InputType> divergenceFunction)
Creates a new instance of
NearestNeighborExhaustive.Learner . |
Modifier and Type | Method and Description |
---|---|
NearestNeighborExhaustive<InputType,OutputType> |
learn(java.util.Collection<? extends InputOutputPair<? extends InputType,OutputType>> data)
The
learn method creates an object of ResultType using
data of type DataType , using some form of "learning" algorithm. |
clone, getDivergenceFunction, setDivergenceFunction
equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
clone
public Learner()
NearestNeighborExhaustive.Learner
.public Learner(DivergenceFunction<? super InputType,? super InputType> divergenceFunction)
NearestNeighborExhaustive.Learner
.divergenceFunction
- The divergence function to use.public NearestNeighborExhaustive<InputType,OutputType> learn(java.util.Collection<? extends InputOutputPair<? extends InputType,OutputType>> data)
BatchLearner
learn
method creates an object of ResultType
using
data of type DataType
, using some form of "learning" algorithm.learn
in interface BatchLearner<java.util.Collection<? extends InputOutputPair<? extends InputType,OutputType>>,NearestNeighborExhaustive<InputType,OutputType>>
data
- The data that the learning algorithm will use to create an
object of ResultType
.