ai.libs.jaicore.ml.core.dataset.sampling.inmemory.factories

Class LocalCaseControlSamplingFactory<I extends IInstance>

java.lang.Object

ai.libs.jaicore.ml.core.dataset.sampling.inmemory.factories.LocalCaseControlSamplingFactory<I>

All Implemented Interfaces:

IRerunnableSamplingAlgorithmFactory<I,LocalCaseControlSampling<I>>, ISamplingAlgorithmFactory<I,LocalCaseControlSampling<I>>

public class LocalCaseControlSamplingFactory<I extends IInstance>
extends java.lang.Object
implements IRerunnableSamplingAlgorithmFactory<I,LocalCaseControlSampling<I>>

Constructor Summary

Constructors

Constructor and Description
LocalCaseControlSamplingFactory()

Method Summary

Modifier and Type	Method and Description
LocalCaseControlSampling<I>	getAlgorithm(int sampleSize, IDataset<I> inputDataset, java.util.Random random) After the necessary config is done, this method returns a fully configured instance of a sampling algorithm.
void	setPreSampleSize(int preSampleSize) Set the size of the sample the pilot estimator will be trained with.
void	setPreviousRun(LocalCaseControlSampling<I> previousRun) Set the previous run of the sampling algorithm, if one occurred, can be set here to get data from it.

Methods inherited from class java.lang.Object

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

Constructor Detail

LocalCaseControlSamplingFactory

public LocalCaseControlSamplingFactory()

Method Detail

setPreviousRun

public void setPreviousRun(LocalCaseControlSampling<I> previousRun)

Description copied from interface: IRerunnableSamplingAlgorithmFactory

Set the previous run of the sampling algorithm, if one occurred, can be set here to get data from it.

Specified by:

setPreviousRun in interface IRerunnableSamplingAlgorithmFactory<I extends IInstance,LocalCaseControlSampling<I extends IInstance>>

Parameters:

previousRun - Algorithm object of the previous of the sampling algorithm.

setPreSampleSize

public void setPreSampleSize(int preSampleSize)

Set the size of the sample the pilot estimator will be trained with. Default is half the dataset.

Parameters:

preSampleSize -

getAlgorithm

public LocalCaseControlSampling<I> getAlgorithm(int sampleSize,
                                                IDataset<I> inputDataset,
                                                java.util.Random random)

Description copied from interface: ISamplingAlgorithmFactory

After the necessary config is done, this method returns a fully configured instance of a sampling algorithm.

Specified by:

getAlgorithm in interface ISamplingAlgorithmFactory<I extends IInstance,LocalCaseControlSampling<I extends IInstance>>

Parameters:

sampleSize - Desired size of the sample that will be created.

inputDataset - Dataset where the sample will be drawn from.

random - Random object to make samples reproducible.

Returns:

Configured sampling algorithm object.