Package ai.libs.jaicore.ml.core.filter.sampling.inmemory.factories

Class LocalCaseControlSamplingFactory

java.lang.Object

ai.libs.jaicore.ml.core.filter.sampling.inmemory.factories.ASampleAlgorithmFactory<org.api4.java.ai.ml.core.dataset.supervised.ILabeledDataset<?>,LocalCaseControlSampling>

ai.libs.jaicore.ml.core.filter.sampling.inmemory.factories.LocalCaseControlSamplingFactory

All Implemented Interfaces:

IRerunnableSamplingAlgorithmFactory<org.api4.java.ai.ml.core.dataset.supervised.ILabeledDataset<?>,LocalCaseControlSampling>, ISamplingAlgorithmFactory<org.api4.java.ai.ml.core.dataset.supervised.ILabeledDataset<?>,LocalCaseControlSampling>, org.api4.java.common.reconstruction.IReconstructible

public class LocalCaseControlSamplingFactory
extends ASampleAlgorithmFactory<org.api4.java.ai.ml.core.dataset.supervised.ILabeledDataset<?>,LocalCaseControlSampling>
implements IRerunnableSamplingAlgorithmFactory<org.api4.java.ai.ml.core.dataset.supervised.ILabeledDataset<?>,LocalCaseControlSampling>

Constructor Summary

Constructors

Constructor	Description
LocalCaseControlSamplingFactory()

Method Summary

Modifier and Type	Method	Description
LocalCaseControlSampling	getAlgorithm(int sampleSize, org.api4.java.ai.ml.core.dataset.supervised.ILabeledDataset<?> inputDataset, java.util.Random random)	After the necessary config is done, this method returns a fully configured instance of a sampling algorithm.
org.api4.java.ai.ml.classification.IClassifier	getPilot()
void	setPilot(org.api4.java.ai.ml.classification.IClassifier pilot)
void	setPreSampleSize(int preSampleSize)	Set the size of the sample the pilot estimator will be trained with.
void	setPreviousRun(LocalCaseControlSampling 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 ai.libs.jaicore.ml.core.filter.sampling.inmemory.factories.ASampleAlgorithmFactory

addInstruction, create, getAlgorithm, getConstructionInstruction, getConstructionPlan, getRandom, getSampleSize, getSeed, setRandom, setSampleSize, setSeed

Methods inherited from class java.lang.Object

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

Methods inherited from interface ai.libs.jaicore.ml.core.filter.sampling.inmemory.factories.interfaces.ISamplingAlgorithmFactory

getAlgorithm

Constructor Detail

LocalCaseControlSamplingFactory

public LocalCaseControlSamplingFactory()

Method Detail

setPreviousRun

public void setPreviousRun(LocalCaseControlSampling 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<org.api4.java.ai.ml.core.dataset.supervised.ILabeledDataset<?>,LocalCaseControlSampling>

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 -

getPilot

public org.api4.java.ai.ml.classification.IClassifier getPilot()

setPilot

public void setPilot(org.api4.java.ai.ml.classification.IClassifier pilot)

getAlgorithm

public LocalCaseControlSampling getAlgorithm(int sampleSize,
                                             org.api4.java.ai.ml.core.dataset.supervised.ILabeledDataset<?> 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<org.api4.java.ai.ml.core.dataset.supervised.ILabeledDataset<?>,LocalCaseControlSampling>

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.