Modifier and Type | Method and Description |
---|---|
SelectedTag |
FPGrowth.getMetricType()
Get the metric type to use.
|
SelectedTag |
Apriori.getMetricType()
Get the metric type
|
SelectedTag |
Tertius.getMissingValues()
Get the value of missingValues.
|
SelectedTag |
Tertius.getNegation()
Get the value of negation.
|
SelectedTag |
Tertius.getValuesOutput()
Get the value of valuesOutput.
|
Modifier and Type | Method and Description |
---|---|
void |
FPGrowth.setMetricType(SelectedTag d)
Set the metric type to use.
|
void |
Apriori.setMetricType(SelectedTag d)
Set the metric type for ranking rules
|
void |
Tertius.setMissingValues(SelectedTag v)
Set the value of missingValues.
|
void |
Tertius.setNegation(SelectedTag v)
Set the value of negation.
|
void |
Tertius.setValuesOutput(SelectedTag v)
Set the value of valuesOutput.
|
Modifier and Type | Method and Description |
---|---|
SelectedTag |
ScatterSearchV1.getCombination()
Get the combination
|
SelectedTag |
CostSensitiveASEvaluation.getCostMatrixSource()
Gets the source location method of the cost matrix.
|
SelectedTag |
BestFirst.getDirection()
Get the search direction
|
SelectedTag |
SVMAttributeEval.getFilterType()
Get the filtering mode passed to SMO
|
SelectedTag |
RaceSearch.getFoldsType()
Get the xfold type
|
SelectedTag |
LinearForwardSelection.getForwardSelectionMethod()
Get the search direction
|
SelectedTag |
RaceSearch.getRaceType()
Get the race type
|
SelectedTag |
SubsetSizeForwardSelection.getType()
Get the type
|
SelectedTag |
LinearForwardSelection.getType()
Get the type
|
Modifier and Type | Method and Description |
---|---|
void |
ScatterSearchV1.setCombination(SelectedTag c)
Set the kind of combination
|
void |
CostSensitiveASEvaluation.setCostMatrixSource(SelectedTag newMethod)
Sets the source location of the cost matrix.
|
void |
BestFirst.setDirection(SelectedTag d)
Set the search direction
|
void |
SVMAttributeEval.setFilterType(SelectedTag newType)
The filtering mode to pass to SMO
|
void |
RaceSearch.setFoldsType(SelectedTag d)
Set the xfold type
|
void |
LinearForwardSelection.setForwardSelectionMethod(SelectedTag d)
Set the search direction
|
void |
RaceSearch.setRaceType(SelectedTag d)
Set the race type
|
void |
SubsetSizeForwardSelection.setType(SelectedTag t)
Set the type
|
void |
LinearForwardSelection.setType(SelectedTag t)
Set the type
|
Modifier and Type | Method and Description |
---|---|
SelectedTag |
BayesianLogisticRegression.getHyperparameterSelection()
Get the method used to select the hyperparameter
|
SelectedTag |
BayesianLogisticRegression.getPriorClass()
Get the type of prior to use.
|
Modifier and Type | Method and Description |
---|---|
void |
BayesianLogisticRegression.setHyperparameterSelection(SelectedTag newMethod)
Set the method used to select the hyperparameter
|
void |
BayesianLogisticRegression.setPriorClass(SelectedTag newMethod)
Set the type of prior to use.
|
Modifier and Type | Method and Description |
---|---|
SelectedTag |
GlobalScoreSearchAlgorithm.getCVType()
get cross validation strategy to be used in searching for networks.
|
Modifier and Type | Method and Description |
---|---|
void |
GlobalScoreSearchAlgorithm.setCVType(SelectedTag newCVType)
set cross validation strategy to be used in searching for networks.
|
Modifier and Type | Method and Description |
---|---|
SelectedTag |
LocalScoreSearchAlgorithm.getScoreType()
get quality measure to be used in searching for networks.
|
Modifier and Type | Method and Description |
---|---|
void |
LocalScoreSearchAlgorithm.setScoreType(SelectedTag newScoreType)
set quality measure to be used in searching for networks.
|
Modifier and Type | Method and Description |
---|---|
SelectedTag |
LinearRegression.getAttributeSelectionMethod()
Gets the method used to select attributes for use in the
linear regression.
|
SelectedTag |
PaceRegression.getEstimator()
Gets the estimator
|
SelectedTag |
SMO.getFilterType()
Gets how the training data will be transformed.
|
SelectedTag |
SMOreg.getFilterType()
Gets how the training data will be transformed.
|
SelectedTag |
GaussianProcesses.getFilterType()
Gets how the training data will be transformed.
|
SelectedTag |
LibSVM.getKernelType()
Gets type of kernel function
|
SelectedTag |
SPegasos.getLossFunction()
Get the current loss function.
|
SelectedTag |
LibSVM.getSVMType()
Gets type of SVM
|
SelectedTag |
LibLINEAR.getSVMType()
Gets type of SVM
|
Modifier and Type | Method and Description |
---|---|
void |
LinearRegression.setAttributeSelectionMethod(SelectedTag method)
Sets the method used to select attributes for use in the
linear regression.
|
void |
PaceRegression.setEstimator(SelectedTag estimator)
Sets the estimator.
|
void |
SMO.setFilterType(SelectedTag newType)
Sets how the training data will be transformed.
|
void |
SMOreg.setFilterType(SelectedTag newType)
Sets how the training data will be transformed.
|
void |
GaussianProcesses.setFilterType(SelectedTag newType)
Sets how the training data will be transformed.
|
void |
LibSVM.setKernelType(SelectedTag value)
Sets type of kernel function (default KERNELTYPE_RBF)
|
void |
SPegasos.setLossFunction(SelectedTag function)
Set the loss function to use.
|
void |
LibSVM.setSVMType(SelectedTag value)
Sets type of SVM (default SVMTYPE_C_SVC)
|
void |
LibLINEAR.setSVMType(SelectedTag value)
Sets type of SVM (default SVMTYPE_L2)
|
Modifier and Type | Method and Description |
---|---|
SelectedTag |
StringKernel.getPruningMethod()
Gets the method used for pruning.
|
Modifier and Type | Method and Description |
---|---|
void |
StringKernel.setPruningMethod(SelectedTag value)
Sets the method used to for pruning.
|
Modifier and Type | Method and Description |
---|---|
SelectedTag |
IBk.getDistanceWeighting()
Gets the distance weighting method used.
|
SelectedTag |
KStar.getMissingMode()
Gets the method to use for handling missing values.
|
Modifier and Type | Method and Description |
---|---|
void |
IBk.setDistanceWeighting(SelectedTag newMethod)
Sets the distance weighting method used.
|
void |
KStar.setMissingMode(SelectedTag newMode)
Sets the method to use for handling missing values.
|
Modifier and Type | Method and Description |
---|---|
SelectedTag |
Vote.getCombinationRule()
Gets the combination rule used
|
SelectedTag |
CostSensitiveClassifier.getCostMatrixSource()
Gets the source location method of the cost matrix.
|
SelectedTag |
MetaCost.getCostMatrixSource()
Gets the source location method of the cost matrix.
|
SelectedTag |
ThresholdSelector.getDesignatedClass()
Gets the method to determine which class value to optimize.
|
SelectedTag |
GridSearch.getEvaluation()
Gets the criterion used for evaluating the classifier performance.
|
SelectedTag |
ThresholdSelector.getEvaluationMode()
Gets the evaluation mode used.
|
SelectedTag |
ThresholdSelector.getMeasure()
get measure used for determining threshold
|
SelectedTag |
MultiClassClassifier.getMethod()
Gets the method used.
|
SelectedTag |
RacedIncrementalLogitBoost.getPruningType()
Get the pruning type
|
SelectedTag |
ThresholdSelector.getRangeCorrection()
Gets the confidence range correction mode used.
|
SelectedTag |
GridSearch.getTraversal()
Gets the type of traversal for the grid.
|
Modifier and Type | Method and Description |
---|---|
void |
Vote.setCombinationRule(SelectedTag newRule)
Sets the combination rule to use.
|
void |
CostSensitiveClassifier.setCostMatrixSource(SelectedTag newMethod)
Sets the source location of the cost matrix.
|
void |
MetaCost.setCostMatrixSource(SelectedTag newMethod)
Sets the source location of the cost matrix.
|
void |
ThresholdSelector.setDesignatedClass(SelectedTag newMethod)
Sets the method to determine which class value to optimize.
|
void |
GridSearch.setEvaluation(SelectedTag value)
Sets the criterion to use for evaluating the classifier performance.
|
void |
ThresholdSelector.setEvaluationMode(SelectedTag newMethod)
Sets the evaluation mode used.
|
void |
ThresholdSelector.setMeasure(SelectedTag newMeasure)
set measure used for determining threshold
|
void |
MultiClassClassifier.setMethod(SelectedTag newMethod)
Sets the method used.
|
void |
RacedIncrementalLogitBoost.setPruningType(SelectedTag pruneType)
Set the pruning type
|
void |
ThresholdSelector.setRangeCorrection(SelectedTag newMethod)
Sets the confidence range correction mode used.
|
void |
GridSearch.setTraversal(SelectedTag value)
Sets the type of traversal for the grid.
|
Modifier and Type | Method and Description |
---|---|
SelectedTag |
MILR.getAlgorithmType()
Gets the type of algorithm.
|
SelectedTag |
MIDD.getFilterType()
Gets how the training data will be transformed.
|
SelectedTag |
MIOptimalBall.getFilterType()
Gets how the training data will be transformed.
|
SelectedTag |
MDD.getFilterType()
Gets how the training data will be transformed.
|
SelectedTag |
MISMO.getFilterType()
Gets how the training data will be transformed.
|
SelectedTag |
MIEMDD.getFilterType()
Gets how the training data will be transformed.
|
SelectedTag |
MISVM.getFilterType()
Gets how the training data will be transformed.
|
SelectedTag |
MIWrapper.getMethod()
Get the method used in testing.
|
SelectedTag |
SimpleMI.getTransformMethod()
Get the method used in transformation.
|
SelectedTag |
MIWrapper.getWeightMethod()
Returns the current weighting method for instances.
|
Modifier and Type | Method and Description |
---|---|
void |
MILR.setAlgorithmType(SelectedTag newType)
Sets the algorithm type.
|
void |
MIDD.setFilterType(SelectedTag newType)
Sets how the training data will be transformed.
|
void |
MIOptimalBall.setFilterType(SelectedTag newType)
Sets how the training data will be transformed.
|
void |
MDD.setFilterType(SelectedTag newType)
Sets how the training data will be transformed.
|
void |
MISMO.setFilterType(SelectedTag newType)
Sets how the training data will be transformed.
|
void |
MIEMDD.setFilterType(SelectedTag newType)
Sets how the training data will be transformed.
|
void |
MISVM.setFilterType(SelectedTag newType)
Sets how the training data will be transformed.
|
void |
MIWrapper.setMethod(SelectedTag method)
Set the method used in testing.
|
void |
SimpleMI.setTransformMethod(SelectedTag newMethod)
Set the method used in transformation.
|
void |
MIWrapper.setWeightMethod(SelectedTag method)
The new method for weighting the instances.
|
Modifier and Type | Method and Description |
---|---|
SelectedTag |
DecisionTable.getEvaluationMeasure()
Gets the currently set performance evaluation measure used for selecting
attributes for the decision table
|
Modifier and Type | Method and Description |
---|---|
void |
DecisionTable.setEvaluationMeasure(SelectedTag newMethod)
Sets the performance evaluation measure to use for selecting attributes
for the decision table
|
Modifier and Type | Method and Description |
---|---|
SelectedTag |
FT.getModelType()
Get the type of functional tree model being used.
|
SelectedTag |
BFTree.getPruningStrategy()
Gets the pruning strategy.
|
SelectedTag |
ADTree.getSearchPath()
Gets the method of searching the tree for a new insertion.
|
Modifier and Type | Method and Description |
---|---|
void |
FT.setModelType(SelectedTag newMethod)
Set the Functional Tree type.
|
void |
BFTree.setPruningStrategy(SelectedTag value)
Sets the pruning strategy.
|
void |
ADTree.setSearchPath(SelectedTag newMethod)
Sets the method of searching the tree for a new insertion.
|
Modifier and Type | Method and Description |
---|---|
SelectedTag |
HierarchicalClusterer.getLinkType() |
Modifier and Type | Method and Description |
---|---|
void |
HierarchicalClusterer.setLinkType(SelectedTag newLinkType) |
Modifier and Type | Method and Description |
---|---|
SelectedTag |
Agrawal.getFunction()
Gets the function for generating the data.
|
Modifier and Type | Method and Description |
---|---|
void |
Agrawal.setFunction(SelectedTag value)
Sets the function for generating the data.
|
Modifier and Type | Method and Description |
---|---|
SelectedTag |
SubspaceClusterDefinition.getClusterSubType()
Gets the cluster sub type.
|
SelectedTag |
SubspaceClusterDefinition.getClusterType()
Gets the cluster type.
|
SelectedTag |
BIRCHCluster.getInputOrder()
Gets the input order.
|
SelectedTag |
BIRCHCluster.getPattern()
Gets the pattern type.
|
Modifier and Type | Method and Description |
---|---|
void |
SubspaceClusterDefinition.setClusterSubType(SelectedTag value)
Sets the cluster sub type.
|
void |
SubspaceClusterDefinition.setClusterType(SelectedTag value)
Sets the cluster type.
|
void |
BIRCHCluster.setInputOrder(SelectedTag value)
Sets the input order.
|
void |
BIRCHCluster.setPattern(SelectedTag value)
Sets the pattern type.
|
Modifier and Type | Method and Description |
---|---|
SelectedTag |
PLSFilter.getAlgorithm()
Gets the type of algorithm to use
|
SelectedTag |
PLSFilter.getPreprocessing()
Gets the type of preprocessing to use
|
Modifier and Type | Method and Description |
---|---|
void |
PLSFilter.setAlgorithm(SelectedTag value)
Sets the type of algorithm to use
|
void |
PLSFilter.setPreprocessing(SelectedTag value)
Sets the type of preprocessing to use
|
Modifier and Type | Method and Description |
---|---|
SelectedTag |
Wavelet.getAlgorithm()
Gets the type of algorithm to use
|
SelectedTag |
Add.getAttributeType()
Gets the type of attribute to generate.
|
SelectedTag |
RemoveType.getAttributeType()
Gets the attribute type to be deleted by the filter.
|
SelectedTag |
RandomProjection.getDistribution()
Returns the current distribution that'll be used for calculating the random
matrix
|
SelectedTag |
StringToWordVector.getNormalizeDocLength()
Gets whether if the word frequencies for a document (instance) should
be normalized or not.
|
SelectedTag |
Wavelet.getPadding()
Gets the type of Padding to use
|
SelectedTag |
MultiInstanceToPropositional.getWeightMethod()
Returns the current weighting method for instances.
|
Modifier and Type | Method and Description |
---|---|
void |
Wavelet.setAlgorithm(SelectedTag value)
Sets the type of algorithm to use
|
void |
Add.setAttributeType(SelectedTag value)
Sets the type of attribute to generate.
|
void |
RemoveType.setAttributeType(SelectedTag type)
Sets the attribute type to be deleted by the filter.
|
void |
RandomProjection.setDistribution(SelectedTag newDstr)
Sets the distribution to use for calculating the random matrix
|
void |
StringToWordVector.setNormalizeDocLength(SelectedTag newType)
Sets whether if the word frequencies for a document (instance) should
be normalized or not.
|
void |
Wavelet.setPadding(SelectedTag value)
Sets the type of Padding to use
|
void |
MultiInstanceToPropositional.setWeightMethod(SelectedTag method)
The new method for weighting the instances.
|
Modifier and Type | Method and Description |
---|---|
SelectedTag |
Main.getGUIType()
Gets the currently set type of GUI to display.
|
Modifier and Type | Method and Description |
---|---|
void |
Main.setGUIType(SelectedTag value)
Sets the type of GUI to use.
|
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