public abstract class AbstractMLPlanSingleLabelBuilder extends AbstractMLPlanBuilder
| Modifier and Type | Field and Description |
|---|---|
protected static ai.libs.jaicore.ml.core.evaluation.measure.IMeasure<java.lang.Double,java.lang.Double> |
LOSS_FUNCTION |
protected static int |
SEARCH_NUM_MC_ITERATIONS |
protected static double |
SEARCH_TRAIN_FOLD_SIZE |
protected static int |
SELECTION_NUM_MC_ITERATIONS |
protected static double |
SELECTION_TRAIN_FOLD_SIZE |
| Modifier | Constructor and Description |
|---|---|
protected |
AbstractMLPlanSingleLabelBuilder() |
| Modifier and Type | Method and Description |
|---|---|
protected ai.libs.jaicore.ml.weka.dataset.splitter.IDatasetSplitter |
getDefaultDatasetSplitter() |
AbstractMLPlanSingleLabelBuilder |
withMonteCarloCrossValidationInSearchPhase(int numIterations,
double trainFoldSize,
ai.libs.jaicore.ml.core.evaluation.measure.IMeasure<java.lang.Double,java.lang.Double> lossFunction)
Configure ML-Plan to use MCCV for the given number of iterations, train fold size and loss function in the search phase.
|
AbstractMLPlanSingleLabelBuilder |
withMonteCarloCrossValidationInSelectionPhase(int numIterations,
double trainFoldSize,
ai.libs.jaicore.ml.core.evaluation.measure.IMeasure<java.lang.Double,java.lang.Double> lossFunction)
Configure ML-Plan to use MCCV for the given number of iterations, train fold size and loss function in the selection phase.
|
AbstractMLPlanSingleLabelBuilder |
withPerformanceMeasure(ai.libs.jaicore.ml.core.evaluation.measure.IMeasure<java.lang.Double,java.lang.Double> lossFunction)
Sets the performance measure to evaluate a candidate solution's generalization performance.
|
build, build, forMeka, forSKLearn, forWeka, getAlgorithmConfig, getCandidateEvaluationTimeOut, getClassifierEvaluationInSearchPhase, getClassifierEvaluationInSelectionPhase, getClassifierFactory, getComponents, getDBAdapter, getHASCOFactory, getLoggerName, getNodeEvaluationTimeOut, getPerformanceMeasureName, getRequestedInterface, getSearchEvaluatorFactory, getSearchSelectionDatasetSplitter, getSearchSpaceConfigFile, getSelectionEvaluatorFactory, getTimeOut, getUseCache, prepareNodeEvaluatorInFactoryWithData, setLoggerName, setPerformanceMeasureName, withAlgorithmConfig, withAlgorithmConfigFile, withCandidateEvaluationTimeOut, withClassifierFactory, withDataset, withDatasetSplitterForSearchSelectionSplit, withNodeEvaluationTimeOut, withNumCpus, withPreferredComponentsFile, withPreferredNodeEvaluator, withRandomCompletionBasedBestFirstSearch, withRequestedInterface, withSearchFactory, withSearchPhaseEvaluatorFactory, withSearchSpaceConfigFile, withSelectionPhaseEvaluatorFactory, withTimeOutprotected static final int SEARCH_NUM_MC_ITERATIONS
protected static final double SEARCH_TRAIN_FOLD_SIZE
protected static final int SELECTION_NUM_MC_ITERATIONS
protected static final double SELECTION_TRAIN_FOLD_SIZE
protected static final ai.libs.jaicore.ml.core.evaluation.measure.IMeasure<java.lang.Double,java.lang.Double> LOSS_FUNCTION
public AbstractMLPlanSingleLabelBuilder withMonteCarloCrossValidationInSearchPhase(int numIterations, double trainFoldSize, ai.libs.jaicore.ml.core.evaluation.measure.IMeasure<java.lang.Double,java.lang.Double> lossFunction)
numIterations - The number of iterations of the MCCV.trainFoldSize - The portion of the data that is to be used as training data.lossFunction - The loss function to evaluate the performance of the classifier.public AbstractMLPlanSingleLabelBuilder withMonteCarloCrossValidationInSelectionPhase(int numIterations, double trainFoldSize, ai.libs.jaicore.ml.core.evaluation.measure.IMeasure<java.lang.Double,java.lang.Double> lossFunction)
numIterations - The number of iterations of the MCCV.trainFoldSize - The portion of the data that is to be used as training data.lossFunction - The loss function to evaluate the performance of the classifier.public AbstractMLPlanSingleLabelBuilder withPerformanceMeasure(ai.libs.jaicore.ml.core.evaluation.measure.IMeasure<java.lang.Double,java.lang.Double> lossFunction)
lossFunction - The loss function to be used.protected ai.libs.jaicore.ml.weka.dataset.splitter.IDatasetSplitter getDefaultDatasetSplitter()