public class ExtrapolatedSaturationPointEvaluator<I extends IInstance> extends java.lang.Object implements IClassifierEvaluator
| Constructor and Description |
|---|
ExtrapolatedSaturationPointEvaluator(int[] anchorpoints,
ISamplingAlgorithmFactory<I,? extends ASamplingAlgorithm<I>> samplingAlgorithmFactory,
IDataset<I> train,
double trainSplitForAnchorpointsMeasurement,
LearningCurveExtrapolationMethod extrapolationMethod,
long seed,
IDataset<I> test)
Create a classifier evaluator with an accuracy measurement at the
extrapolated learning curves saturation point.
|
| Modifier and Type | Method and Description |
|---|---|
java.lang.Double |
evaluate(weka.classifiers.Classifier classifier) |
void |
setEpsilon(double epsilon) |
public ExtrapolatedSaturationPointEvaluator(int[] anchorpoints,
ISamplingAlgorithmFactory<I,? extends ASamplingAlgorithm<I>> samplingAlgorithmFactory,
IDataset<I> train,
double trainSplitForAnchorpointsMeasurement,
LearningCurveExtrapolationMethod extrapolationMethod,
long seed,
IDataset<I> test)
anchorpoints - Anchorpoints for the learning curve extrapolation.samplingAlgorithmFactory - Subsampling factory for a subsampler to create samples at the
given anchorpoints.train - Dataset predict the learning curve with and where the subsample
for the measurement is drawn from.trainSplitForAnchorpointsMeasurement - Ratio to split the subsamples at the anchorpoints into train and
test.extrapolationMethod - Method to extrapolate a learning curve from the accuracy
measurements at the anchorpoints.seed - Random seed.test - Test dataset to measure the accuracy.public void setEpsilon(double epsilon)
public java.lang.Double evaluate(weka.classifiers.Classifier classifier)
throws java.lang.InterruptedException,
ai.libs.jaicore.basic.algorithm.exceptions.ObjectEvaluationFailedException
evaluate in interface ai.libs.jaicore.basic.IObjectEvaluator<weka.classifiers.Classifier,java.lang.Double>java.lang.InterruptedExceptionai.libs.jaicore.basic.algorithm.exceptions.ObjectEvaluationFailedException