Class ClassifierWeightedSampling<I extends ILabeledInstance<?>,D extends IOrderedDataset<I>>
- java.lang.Object
-
- ai.libs.jaicore.basic.algorithm.AAlgorithm<D,D>
-
- ai.libs.jaicore.ml.core.dataset.sampling.inmemory.ASamplingAlgorithm<I,D>
-
- ai.libs.jaicore.ml.core.dataset.sampling.inmemory.casecontrol.CaseControlLikeSampling<I,D>
-
- ai.libs.jaicore.ml.core.dataset.sampling.inmemory.casecontrol.ClassifierWeightedSampling<I,D>
-
- Type Parameters:
I-
- All Implemented Interfaces:
ai.libs.jaicore.basic.algorithm.IAlgorithm<D,D>,ai.libs.jaicore.basic.Cancelable,ai.libs.jaicore.basic.ILoggingCustomizable,ISamplingAlgorithm<D>,java.lang.Iterable<ai.libs.jaicore.basic.algorithm.events.AlgorithmEvent>,java.util.concurrent.Callable<D>,java.util.Iterator<ai.libs.jaicore.basic.algorithm.events.AlgorithmEvent>
public class ClassifierWeightedSampling<I extends ILabeledInstance<?>,D extends IOrderedDataset<I>> extends CaseControlLikeSampling<I,D>
The idea behind this Sampling method is to weight instances depended on the way a pilot estimator p classified them. Instances that p classified right but was unsure contain the most information and are most likely to be chosen. Instances that p is very sure about and Instances that p is quite sure about their actual class and classified them falsely, are medium likely to be chosen. Instances that p is very unsure about their actual class and classified them falsely are not likely to be chosen. Note that any instance still has a base probability to be chosen.
-
-
Field Summary
-
Fields inherited from class ai.libs.jaicore.ml.core.dataset.sampling.inmemory.casecontrol.CaseControlLikeSampling
probabilityBoundaries, rand
-
Fields inherited from class ai.libs.jaicore.ml.core.dataset.sampling.inmemory.ASamplingAlgorithm
sample, sampleSize
-
-
Constructor Summary
Constructors Constructor Description ClassifierWeightedSampling(java.util.Random rand, weka.core.Instances instances, D input)
-
Method Summary
All Methods Instance Methods Concrete Methods Modifier and Type Method Description ai.libs.jaicore.basic.algorithm.events.AlgorithmEventnextWithException()-
Methods inherited from class ai.libs.jaicore.ml.core.dataset.sampling.inmemory.casecontrol.CaseControlLikeSampling
calculateInstanceBoundaries, countClassOccurrences, getProbabilityBoundaries, setProbabilityBoundaries
-
Methods inherited from class ai.libs.jaicore.ml.core.dataset.sampling.inmemory.ASamplingAlgorithm
call, doInactiveStep, getComplement, setSampleSize
-
Methods inherited from class ai.libs.jaicore.basic.algorithm.AAlgorithm
activate, announceTimeoutDetected, avoidReinterruptionOnShutdownOnCurrentThread, cancel, checkAndConductTermination, checkTermination, computeTimeoutAware, getActivationTime, getConfig, getId, getInput, getLoggerName, getNumCPUs, getRemainingTimeToDeadline, getState, getTimeout, getTimeoutPrecautionOffset, hasNext, hasThreadBeenInterruptedDuringShutdown, interruptThreadAsPartOfShutdown, isCanceled, isShutdownInitialized, isStopCriterionSatisfied, isTimeouted, iterator, next, post, registerActiveThread, registerListener, resolveShutdownInterruptOnCurrentThread, setConfig, setLoggerName, setMaxNumThreads, setNumCPUs, setState, setTimeout, setTimeout, setTimeoutPrecautionOffset, shutdown, terminate, unregisterActiveThread, unregisterThreadAndShutdown
-
Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
-
-
-
-
Constructor Detail
-
ClassifierWeightedSampling
public ClassifierWeightedSampling(java.util.Random rand, weka.core.Instances instances, D input)
-
-
Method Detail
-
nextWithException
public ai.libs.jaicore.basic.algorithm.events.AlgorithmEvent nextWithException() throws java.lang.InterruptedException, ai.libs.jaicore.basic.algorithm.AlgorithmExecutionCanceledException, ai.libs.jaicore.basic.algorithm.exceptions.AlgorithmException- Throws:
java.lang.InterruptedExceptionai.libs.jaicore.basic.algorithm.AlgorithmExecutionCanceledExceptionai.libs.jaicore.basic.algorithm.exceptions.AlgorithmException
-
-