A C D E F G I K L M N O P R S T U V W X

A

AbstractLandmarker - Class in de.dfki.madm.mlwizard.landmarking
Abstract superclass of all landmark learner classes, used in the landmark operator.
AbstractLandmarker() - Constructor for class de.dfki.madm.mlwizard.landmarking.AbstractLandmarker
 
actionPerformed(ActionEvent) - Method in class de.dfki.madm.mlwizard.gui.EvaluateTableModel
cancel on one classifier evaluation clicked
add(String, Double) - Method in class de.dfki.madm.mlwizard.metafeatures.MetaFeaturesOperator.MetaFeatures
 
addAccuracy(String, Double) - Method in class de.dfki.madm.mlwizard.Classifier
 
addChangeListener(ChangeListener) - Method in class de.dfki.madm.mlwizard.gui.EvaluateTableModel
 
addClassifier(Classifier, String, String, KnowledgeBase) - Static method in class de.dfki.madm.mlwizard.Administrator
adds a classifier with pre-computed accuracies and parameters
addClassifier(Classifier, boolean) - Method in class de.dfki.madm.mlwizard.KnowledgeBase
adds a classifier to this knowledge base
addDataset(ExampleSet, String, boolean) - Method in class de.dfki.madm.mlwizard.KnowledgeBase
adds a new dataset to the knowledge base by computing its meta-features, evaluating all classifiers, and updating the accuracy prediction models as well as the set of selected meta-features
addDatasets(String, KnowledgeBase, boolean) - Static method in class de.dfki.madm.mlwizard.Administrator
adds a complete folder of datasets (not recursively) in the XRFF format to the knowledge base.
addOperator(Process, Class<T>, Operator) - Static method in class de.dfki.madm.mlwizard.functionality.SystemConstructor
creates an operator and adds it to the process and connect its first input with the first output of the previous operator
addParameters(String, ParameterSet) - Method in class de.dfki.madm.mlwizard.Classifier
 
Administrator - Class in de.dfki.madm.mlwizard
 
Administrator() - Constructor for class de.dfki.madm.mlwizard.Administrator
 
apply(ExampleSet) - Method in class de.dfki.madm.mlwizard.metafeatures.MetaFeaturesOperator
 
AttributeStats - Class in de.dfki.madm.mlwizard.metafeatures
 
AttributeStats(ExampleSet, ExampleSet, Attribute) - Constructor for class de.dfki.madm.mlwizard.metafeatures.AttributeStats
 
AutomaticSystemConstructionWizard - Class in de.dfki.madm.mlwizard.gui
This initializes the Wizard and starts with selection of a repository location.
AutomaticSystemConstructionWizard(String, Object...) - Constructor for class de.dfki.madm.mlwizard.gui.AutomaticSystemConstructionWizard
 
AverageNodeLm - Class in de.dfki.madm.mlwizard.landmarking
This landmark learner is an Average landmark learner, where a DecisionStumpLearner for each attribute is created and then the performance average is calculated.
AverageNodeLm(ExampleSet, Map<String, String>) - Constructor for class de.dfki.madm.mlwizard.landmarking.AverageNodeLm
 
awaitTermination() - Method in class de.dfki.madm.mlwizard.functionality.Evaluator
 
awaitTermination(long, TimeUnit) - Method in class de.dfki.madm.mlwizard.KnowledgeBase
 

C

cancelThread(String) - Method in class de.dfki.madm.mlwizard.functionality.Evaluator
cancels the evaluation thread of a given classifier
cancelThreads() - Method in class de.dfki.madm.mlwizard.functionality.Evaluator
cancel all evaluation threads
Classifier - Class in de.dfki.madm.mlwizard
 
Classifier(String, Class<? extends AbstractLearner>, List<String[]>, List<String[]>) - Constructor for class de.dfki.madm.mlwizard.Classifier
 
Classifier(String, String, String, List<String[]>, List<String[]>) - Constructor for class de.dfki.madm.mlwizard.Classifier
 
Classifier(String, Class<? extends AbstractLearner>, List<String[]>, List<String[]>, Classifier) - Constructor for class de.dfki.madm.mlwizard.Classifier
 
combineParameterSets(ParameterSet, ParameterSet, PerformanceVector) - Static method in class de.dfki.madm.mlwizard.Util
combine two parameter sets
CommandLineInterface - Class in de.dfki.madm.mlwizard.cli
 
CommandLineInterface() - Constructor for class de.dfki.madm.mlwizard.cli.CommandLineInterface
 
compute(ExampleSet) - Method in class de.dfki.madm.mlwizard.metafeatures.MetaFeaturesOperator
computes the meta-features of a given dataset
computeFrequencies(ExampleSet, Attribute) - Method in class de.dfki.madm.mlwizard.metafeatures.AttributeStats
 
computeStatistics(ExampleSet, Attribute) - Method in class de.dfki.madm.mlwizard.metafeatures.AttributeStats
 
conditionalFrequencies - Variable in class de.dfki.madm.mlwizard.metafeatures.AttributeStats
 
construct(ExampleSet, Classifier, ParameterSet, String, OutputStream) - Static method in class de.dfki.madm.mlwizard.cli.CommandLineInterface
 
createExampleSet(MetaFeaturesOperator.MetaFeatures) - Static method in class de.dfki.madm.mlwizard.metafeatures.MetaFeaturesOperator
creates an example set out of a MetaFeatures object
createOptimizer(RandomGenerator) - Method in class de.dfki.madm.mlwizard.optimization.ESOptimizationPaREn
 
createProcess(Classifier, ParameterSet, String) - Static method in class de.dfki.madm.mlwizard.functionality.SystemConstructor
 
createProcess(Classifier, ParameterSet, String, boolean) - Static method in class de.dfki.madm.mlwizard.functionality.SystemConstructor
creates a complete process of creating a classification model for the given classifier, parameter set and dataset

D

dataSetRepositoryLocationStep - Variable in class de.dfki.madm.mlwizard.gui.AutomaticSystemConstructionWizard
 
DATASETS_FOLDER - Static variable in class de.dfki.madm.mlwizard.Util
 
de.dfki.madm.mlwizard - package de.dfki.madm.mlwizard
 
de.dfki.madm.mlwizard.cli - package de.dfki.madm.mlwizard.cli
 
de.dfki.madm.mlwizard.functionality - package de.dfki.madm.mlwizard.functionality
 
de.dfki.madm.mlwizard.gui - package de.dfki.madm.mlwizard.gui
 
de.dfki.madm.mlwizard.landmarking - package de.dfki.madm.mlwizard.landmarking
 
de.dfki.madm.mlwizard.metafeatures - package de.dfki.madm.mlwizard.metafeatures
 
de.dfki.madm.mlwizard.optimization - package de.dfki.madm.mlwizard.optimization
 
DecisionNodeLm - Class in de.dfki.madm.mlwizard.landmarking
This landmark learner is a DecisionStumpLearner, where a single decision node is chosen according to the highest gain ratio.
DecisionNodeLm(ExampleSet, Map<String, String>) - Constructor for class de.dfki.madm.mlwizard.landmarking.DecisionNodeLm
 
determineOptimalMetaFeaturesForParameterPrediction(ExampleSet) - Method in class de.dfki.madm.mlwizard.Classifier
 
dev - Variable in class de.dfki.madm.mlwizard.metafeatures.AttributeStats
 
dispose() - Method in class de.dfki.madm.mlwizard.gui.AutomaticSystemConstructionWizard
 
dist(Example, Example) - Static method in class de.dfki.madm.mlwizard.Util
computes the squared euclidean distance between a and b (omits the square root calculation for efficiency reasons)
dist(Example, Example, AttributeWeights) - Static method in class de.dfki.madm.mlwizard.Util
computes the squared euclidean distance between a and b (omits the square root calculation for efficiency reasons) using the given set of attributes only
dist(Example, Example, long) - Static method in class de.dfki.madm.mlwizard.Util
computes the squared euclidean distance between a and b (omits the square root calculation for efficiency reasons) using the given binary mask of attribute
doInBackground() - Method in class de.dfki.madm.mlwizard.functionality.Evaluator.EvaluateSwingThread
 

E

ESOptimizationPaREn - Class in de.dfki.madm.mlwizard.optimization
override of the GA that uses a faked random generator to introduce defined start points
ESOptimizationPaREn(OperatorDescription) - Constructor for class de.dfki.madm.mlwizard.optimization.ESOptimizationPaREn
 
evaluate(KnowledgeBase) - Method in class de.dfki.madm.mlwizard.Classifier
 
evaluate(Iterable<Classifier>, Example, KnowledgeBase, ExampleSet, int) - Method in class de.dfki.madm.mlwizard.functionality.Evaluator
 
evaluate(Iterable<Classifier>, Example, KnowledgeBase, ExampleSet, int, Evaluator.EvaluationListener) - Method in class de.dfki.madm.mlwizard.functionality.Evaluator
evaluates a set of classifier on one dataset
EvaluateTableModel - Class in de.dfki.madm.mlwizard.gui
 
EvaluateTableModel(Regressioner.RegressionResult, JTable, HashMap<String, Boolean>, Evaluator) - Constructor for class de.dfki.madm.mlwizard.gui.EvaluateTableModel
 
evaluateWizardStep - Variable in class de.dfki.madm.mlwizard.gui.AutomaticSystemConstructionWizard
 
Evaluator - Class in de.dfki.madm.mlwizard.functionality
 
Evaluator() - Constructor for class de.dfki.madm.mlwizard.functionality.Evaluator
creates a new evaluator
Evaluator.EvaluateSwingThread - Class in de.dfki.madm.mlwizard.functionality
 
Evaluator.EvaluateSwingThread(Classifier, Process) - Constructor for class de.dfki.madm.mlwizard.functionality.Evaluator.EvaluateSwingThread
 
Evaluator.EvaluationListener - Interface in de.dfki.madm.mlwizard.functionality
 
exception(Exception) - Method in class de.dfki.madm.mlwizard.gui.AutomaticSystemConstructionWizard
 

F

FILE_PATH - Static variable in class de.dfki.madm.mlwizard.Util
 
frequencies - Variable in class de.dfki.madm.mlwizard.metafeatures.AttributeStats
 

G

get(String) - Method in class de.dfki.madm.mlwizard.metafeatures.MetaFeaturesOperator.MetaFeatures
 
getAccuracies() - Method in class de.dfki.madm.mlwizard.Classifier
 
getAccuracy() - Method in class de.dfki.madm.mlwizard.landmarking.AbstractLandmarker
 
getAnnotations() - Method in class de.dfki.madm.mlwizard.Classifier
 
getAnnotations() - Method in class de.dfki.madm.mlwizard.KnowledgeBase
 
getClassifier(String) - Method in class de.dfki.madm.mlwizard.KnowledgeBase
 
getClassifiers() - Method in class de.dfki.madm.mlwizard.KnowledgeBase
 
getColumnClass(int) - Method in class de.dfki.madm.mlwizard.gui.EvaluateTableModel
 
getColumnClass(int) - Method in class de.dfki.madm.mlwizard.gui.RegressionTableModel
 
getColumnCount() - Method in class de.dfki.madm.mlwizard.gui.EvaluateTableModel
 
getColumnCount() - Method in class de.dfki.madm.mlwizard.gui.RegressionTableModel
 
getColumnName(int) - Method in class de.dfki.madm.mlwizard.gui.EvaluateTableModel
 
getColumnName(int) - Method in class de.dfki.madm.mlwizard.gui.RegressionTableModel
 
getDataSet() - Method in class de.dfki.madm.mlwizard.gui.AutomaticSystemConstructionWizard
 
getDataSetRepositoryLocation() - Method in class de.dfki.madm.mlwizard.gui.AutomaticSystemConstructionWizard
 
getEvaluate() - Method in class de.dfki.madm.mlwizard.gui.RegressionTableModel
 
getExampleFromId(ExampleSet, String) - Static method in class de.dfki.madm.mlwizard.Util
gets the example with the given id using a linear search
getIfEvaluate() - Method in class de.dfki.madm.mlwizard.gui.RegressionTableModel
 
getKnowledgeBase() - Method in class de.dfki.madm.mlwizard.gui.AutomaticSystemConstructionWizard
 
getLeanerInstance() - Method in class de.dfki.madm.mlwizard.Classifier
 
getLearner() - Method in class de.dfki.madm.mlwizard.Classifier
 
getLearnProcess() - Method in class de.dfki.madm.mlwizard.Classifier
 
getMetaFeatures() - Method in class de.dfki.madm.mlwizard.KnowledgeBase
 
getMetaWeightsParameters() - Method in class de.dfki.madm.mlwizard.Classifier
 
getMetaWeightsRegression() - Method in class de.dfki.madm.mlwizard.Classifier
 
getName() - Method in class de.dfki.madm.mlwizard.Classifier
 
getName() - Method in class de.dfki.madm.mlwizard.landmarking.AbstractLandmarker
 
getNominalParmas() - Method in class de.dfki.madm.mlwizard.Classifier
 
getNumericalParams() - Method in class de.dfki.madm.mlwizard.Classifier
 
getOptimizationCase() - Method in class de.dfki.madm.mlwizard.Classifier
 
getParameters() - Method in class de.dfki.madm.mlwizard.Classifier
 
getParameters(String) - Method in class de.dfki.madm.mlwizard.Classifier
 
getPerformanceCriterion(String) - Method in class de.dfki.madm.mlwizard.landmarking.AbstractLandmarker
Returns the performance criterion average value specified.
getPerformanceValues() - Method in class de.dfki.madm.mlwizard.landmarking.AbstractLandmarker
 
getPerformanceVector() - Method in class de.dfki.madm.mlwizard.landmarking.AbstractLandmarker
 
getPreProcess() - Method in class de.dfki.madm.mlwizard.Classifier
 
getPreprocessingModel() - Method in class de.dfki.madm.mlwizard.Classifier
 
getRegressionModel() - Method in class de.dfki.madm.mlwizard.Classifier
 
getRegressionResult() - Method in class de.dfki.madm.mlwizard.gui.RegressionTableModel
 
getRMSE() - Method in class de.dfki.madm.mlwizard.Classifier
 
getRowCount() - Method in class de.dfki.madm.mlwizard.gui.EvaluateTableModel
 
getRowCount() - Method in class de.dfki.madm.mlwizard.gui.RegressionTableModel
 
getSelectedClassifierName() - Method in class de.dfki.madm.mlwizard.gui.EvaluateTableModel
 
getStartPoints(Classifier, Example, int) - Method in class de.dfki.madm.mlwizard.KnowledgeBase
determines the start points for the GA for a given classifier and dataset
getStoredDatasets() - Method in class de.dfki.madm.mlwizard.KnowledgeBase
 
getStream(String) - Static method in class de.dfki.madm.mlwizard.Util
 
getStreamFromFile(String) - Static method in class de.dfki.madm.mlwizard.Util
 
getStreamFromResource(String) - Static method in class de.dfki.madm.mlwizard.Util
 
getTreeBuilder(ExampleSet) - Method in class de.dfki.madm.mlwizard.metafeatures.MetaFeaturesOperator.DecisionTreeLearnerOwn
 
getValueAt(int, int) - Method in class de.dfki.madm.mlwizard.gui.EvaluateTableModel
 
getValueAt(int, int) - Method in class de.dfki.madm.mlwizard.gui.RegressionTableModel
 

I

initClassifiers(KnowledgeBase) - Static method in class de.dfki.madm.mlwizard.Administrator
 
initFinalChecks() - Static method in class de.dfki.madm.mlwizard.PluginInitMLWizard
 
initGui(MainFrame) - Static method in class de.dfki.madm.mlwizard.PluginInitMLWizard
 
initPlugin() - Static method in class de.dfki.madm.mlwizard.PluginInitMLWizard
 
initPluginManager() - Static method in class de.dfki.madm.mlwizard.PluginInitMLWizard
 
initRenderer() - Static method in class de.dfki.madm.mlwizard.PluginInitMLWizard
 
initSplashTexts() - Static method in class de.dfki.madm.mlwizard.PluginInitMLWizard
 
isCellEditable(int, int) - Method in class de.dfki.madm.mlwizard.gui.EvaluateTableModel
 
isCellEditable(int, int) - Method in class de.dfki.madm.mlwizard.gui.RegressionTableModel
 
isComplex() - Method in class de.dfki.madm.mlwizard.Classifier
 
isOneSelected() - Method in class de.dfki.madm.mlwizard.gui.EvaluateTableModel
 

K

KNNLearnerLm - Class in de.dfki.madm.mlwizard.landmarking
This landmark learner uses the KNNLearner, where the k-value is by default 1 except it is changed by the user.
KNNLearnerLm(ExampleSet, Map<String, String>) - Constructor for class de.dfki.madm.mlwizard.landmarking.KNNLearnerLm
 
KnowledgeBase - Class in de.dfki.madm.mlwizard
Central place for all knowledge regarding meta-learning including meta-features and classifiers.
KnowledgeBase() - Constructor for class de.dfki.madm.mlwizard.KnowledgeBase
creates an empty knowledge base
KnowledgeBase.LearningThread - Class in de.dfki.madm.mlwizard
 
KnowledgeBase.LearningThread(Classifier, KnowledgeBase, boolean) - Constructor for class de.dfki.madm.mlwizard.KnowledgeBase.LearningThread
 
kurtosis - Variable in class de.dfki.madm.mlwizard.metafeatures.AttributeStats
 

L

LandmarkingParameters - Class in de.dfki.madm.mlwizard.landmarking
This class contains parameters needed by the LandmarkingOperator and the AbstractLandmarker.
LandmarkingParameters() - Constructor for class de.dfki.madm.mlwizard.landmarking.LandmarkingParameters
 
learn(ExampleSet, Operator, Map<String, String>) - Method in class de.dfki.madm.mlwizard.landmarking.AbstractLandmarker
The Operator learner takes the ExampleSet as input and then its model is applied to the ExampleSet.
learnExampleSet(ExampleSet, Operator, Map<String, String>) - Method in class de.dfki.madm.mlwizard.landmarking.AbstractLandmarker
 

M

main(String[]) - Static method in class de.dfki.madm.mlwizard.Administrator
 
main(String[]) - Static method in class de.dfki.madm.mlwizard.cli.CommandLineInterface
 
mean - Variable in class de.dfki.madm.mlwizard.metafeatures.AttributeStats
 
mergeExampleSets(ExampleSet, ExampleSet) - Static method in class de.dfki.madm.mlwizard.Util
 
metafeatures(ExampleSet, OutputStream) - Static method in class de.dfki.madm.mlwizard.cli.CommandLineInterface
 
metaFeatures - Variable in class de.dfki.madm.mlwizard.functionality.Regressioner.RegressionResult
meta-features of the new dataset
MetaFeaturesOperator - Class in de.dfki.madm.mlwizard.metafeatures
 
MetaFeaturesOperator(OperatorDescription) - Constructor for class de.dfki.madm.mlwizard.metafeatures.MetaFeaturesOperator
 
MetaFeaturesOperator.DecisionTreeLearnerOwn - Class in de.dfki.madm.mlwizard.metafeatures
 
MetaFeaturesOperator.DecisionTreeLearnerOwn(OperatorDescription) - Constructor for class de.dfki.madm.mlwizard.metafeatures.MetaFeaturesOperator.DecisionTreeLearnerOwn
 
MetaFeaturesOperator.MetaFeatures - Class in de.dfki.madm.mlwizard.metafeatures
we use a vector as basis (and no map) since we want to preserve the order of the meta-features (for a better inspection by a user)
MetaFeaturesOperator.MetaFeatures() - Constructor for class de.dfki.madm.mlwizard.metafeatures.MetaFeaturesOperator.MetaFeatures
 
METHOD_PROPORTION_TRANSFORMATION - Static variable in class de.dfki.madm.mlwizard.landmarking.LandmarkingParameters
 
METHOD_RANGE_TRANSFORMATION - Static variable in class de.dfki.madm.mlwizard.landmarking.LandmarkingParameters
 
METHOD_Z_TRANSFORMATION - Static variable in class de.dfki.madm.mlwizard.landmarking.LandmarkingParameters
 
moments - Variable in class de.dfki.madm.mlwizard.metafeatures.AttributeStats
 

N

NaiveBayesLm - Class in de.dfki.madm.mlwizard.landmarking
This landmark learner is a NaiveBayes learner.
NaiveBayesLm(ExampleSet, Map<String, String>) - Constructor for class de.dfki.madm.mlwizard.landmarking.NaiveBayesLm
 
name - Variable in class de.dfki.madm.mlwizard.landmarking.AbstractLandmarker
 
NORMALIZATION_METHODS - Static variable in class de.dfki.madm.mlwizard.landmarking.LandmarkingParameters
 
normalizeExampleSet(ExampleSet, Map<String, String>) - Method in class de.dfki.madm.mlwizard.landmarking.AbstractLandmarker
 
NUMBER_OF_PERFORMANCE_CRITERIA - Static variable in class de.dfki.madm.mlwizard.landmarking.LandmarkingParameters
 

O

optimize(ExampleSet, Example, Collection<Classifier>, int, KnowledgeBase, PrintStream, Regressioner.RegressionResult) - Static method in class de.dfki.madm.mlwizard.cli.CommandLineInterface
 

P

PARAMETER_AVERAGE_NODE_LM - Static variable in class de.dfki.madm.mlwizard.landmarking.LandmarkingParameters
 
PARAMETER_AVERAGE_PERFORMANCES_ONLY - Static variable in class de.dfki.madm.mlwizard.landmarking.LandmarkingParameters
The parameter name for "Indicates if only performance vectors should be averaged or all types of averagable result vectors"
PARAMETER_CROSS_VALIDATION - Static variable in class de.dfki.madm.mlwizard.landmarking.LandmarkingParameters
 
PARAMETER_DECISION_NODE_LM - Static variable in class de.dfki.madm.mlwizard.landmarking.LandmarkingParameters
 
PARAMETER_KNN_K_VALUE - Static variable in class de.dfki.madm.mlwizard.landmarking.LandmarkingParameters
 
PARAMETER_KNN_LM - Static variable in class de.dfki.madm.mlwizard.landmarking.LandmarkingParameters
 
PARAMETER_LEAVE_ONE_OUT - Static variable in class de.dfki.madm.mlwizard.landmarking.LandmarkingParameters
The parameter name for "Set the number of validations to the number of examples.
PARAMETER_LINEAR_DISCRIMINANT_LM - Static variable in class de.dfki.madm.mlwizard.landmarking.LandmarkingParameters
 
PARAMETER_MAX - Static variable in class de.dfki.madm.mlwizard.landmarking.LandmarkingParameters
The parameter name for "The maximum value after normalization"
PARAMETER_MIN - Static variable in class de.dfki.madm.mlwizard.landmarking.LandmarkingParameters
The parameter name for "The minimum value after normalization"
PARAMETER_NAIVEBAYES_LM - Static variable in class de.dfki.madm.mlwizard.landmarking.LandmarkingParameters
 
PARAMETER_NORMALIZATION_METHOD - Static variable in class de.dfki.madm.mlwizard.landmarking.LandmarkingParameters
 
PARAMETER_NORMALIZE_EXAMPLESET - Static variable in class de.dfki.madm.mlwizard.landmarking.LandmarkingParameters
 
PARAMETER_NUMBER_OF_VALIDATIONS - Static variable in class de.dfki.madm.mlwizard.landmarking.LandmarkingParameters
The parameter name for "Number of subsets for the crossvalidation.
PARAMETER_PERFORMANCE_ACCURACY - Variable in class de.dfki.madm.mlwizard.landmarking.AbstractLandmarker
 
PARAMETER_RANDOMLY_CHOSEN_NODE_LM - Static variable in class de.dfki.madm.mlwizard.landmarking.LandmarkingParameters
 
PARAMETER_SAMPLING_TYPE - Static variable in class de.dfki.madm.mlwizard.landmarking.LandmarkingParameters
The parameter name for "Defines the sampling type of the cross validation (linear = consecutive subsets, shuffled = random subsets, stratified = random subsets with class distribution kept constant)"
PARAMETER_WORST_NODE_LM - Static variable in class de.dfki.madm.mlwizard.landmarking.LandmarkingParameters
 
performance - Variable in class de.dfki.madm.mlwizard.landmarking.AbstractLandmarker
 
PluginInitMLWizard - Class in de.dfki.madm.mlwizard
 
PluginInitMLWizard() - Constructor for class de.dfki.madm.mlwizard.PluginInitMLWizard
 
predict(Classifier, ExampleSet) - Static method in class de.dfki.madm.mlwizard.functionality.Regressioner
predict the accuracy for a given classifier and meta-features
predict(KnowledgeBase, ExampleSet) - Static method in class de.dfki.madm.mlwizard.functionality.Regressioner
predicts the accuracies of all classifiers for one dataset
predictions - Variable in class de.dfki.madm.mlwizard.functionality.Regressioner.RegressionResult
accuracy predictions for each classifier
printUsage() - Static method in class de.dfki.madm.mlwizard.cli.CommandLineInterface
 

R

RandomlyChosenNodeLm - Class in de.dfki.madm.mlwizard.landmarking
This landmark learner is a DecisionStumpLearner, where a single decision node is chosen randomly.
RandomlyChosenNodeLm(ExampleSet, Map<String, String>) - Constructor for class de.dfki.madm.mlwizard.landmarking.RandomlyChosenNodeLm
 
read(String) - Static method in class de.dfki.madm.mlwizard.cli.CommandLineInterface
 
read() - Static method in class de.dfki.madm.mlwizard.KnowledgeBase
reads the knowledge from the resource (used within the extension)
read(String, Class<T>) - Static method in class de.dfki.madm.mlwizard.Util
reads an object from a resource or a file.
readDataSet() - Method in class de.dfki.madm.mlwizard.gui.AutomaticSystemConstructionWizard
reads the dataset selected in the dataset repository location step
readDataSet(String) - Static method in class de.dfki.madm.mlwizard.KnowledgeBase
reads a dataset either from resource or from file
readFileAsString(String) - Static method in class de.dfki.madm.mlwizard.Util
 
readFromFile(String, Class<T>) - Static method in class de.dfki.madm.mlwizard.Util
reads an IOObject from a file
readFromRepository(String, Class<T>) - Static method in class de.dfki.madm.mlwizard.Util
 
readFromResource(String, Class<T>) - Static method in class de.dfki.madm.mlwizard.Util
reads an IOObject from a resource
recommend(ExampleSet, KnowledgeBase, PrintStream) - Static method in class de.dfki.madm.mlwizard.cli.CommandLineInterface
 
Regressioner - Class in de.dfki.madm.mlwizard.functionality
 
Regressioner() - Constructor for class de.dfki.madm.mlwizard.functionality.Regressioner
 
Regressioner.RegressionResult - Class in de.dfki.madm.mlwizard.functionality
 
Regressioner.RegressionResult(ExampleSet) - Constructor for class de.dfki.madm.mlwizard.functionality.Regressioner.RegressionResult
 
RegressionTableModel - Class in de.dfki.madm.mlwizard.gui
 
RegressionTableModel(Regressioner.RegressionResult) - Constructor for class de.dfki.madm.mlwizard.gui.RegressionTableModel
 
regressionWizardStep - Variable in class de.dfki.madm.mlwizard.gui.AutomaticSystemConstructionWizard
 
RESOURCE_PATH - Static variable in class de.dfki.madm.mlwizard.Util
 
run() - Method in class de.dfki.madm.mlwizard.KnowledgeBase.LearningThread
 

S

setAccuracies(ExampleSet) - Method in class de.dfki.madm.mlwizard.Classifier
 
setAccuracies(String) - Method in class de.dfki.madm.mlwizard.Classifier
 
setComputing(String) - Method in interface de.dfki.madm.mlwizard.functionality.Evaluator.EvaluationListener
a classifier is now being evaluated
setComputing(String) - Method in class de.dfki.madm.mlwizard.gui.EvaluateTableModel
 
setMetaFeatures(ExampleSet) - Method in class de.dfki.madm.mlwizard.KnowledgeBase
replaces the meta-features
setParameters(ExampleSet) - Method in class de.dfki.madm.mlwizard.Classifier
 
setParameters(String) - Method in class de.dfki.madm.mlwizard.Classifier
 
setPerformance(String, PerformanceVector) - Method in interface de.dfki.madm.mlwizard.functionality.Evaluator.EvaluationListener
the evaluation of a classifier is finished
setPerformance(String, PerformanceVector) - Method in class de.dfki.madm.mlwizard.gui.EvaluateTableModel
 
setStartValues(Iterable<Double>) - Method in class de.dfki.madm.mlwizard.optimization.ESOptimizationPaREn
 
setValueAt(Object, int, int) - Method in class de.dfki.madm.mlwizard.gui.RegressionTableModel
 
skewness - Variable in class de.dfki.madm.mlwizard.metafeatures.AttributeStats
 
stop() - Method in class de.dfki.madm.mlwizard.functionality.Evaluator.EvaluateSwingThread
 
SystemConstructor - Class in de.dfki.madm.mlwizard.functionality
constructs the final classification system
SystemConstructor() - Constructor for class de.dfki.madm.mlwizard.functionality.SystemConstructor
 

T

trainRegressionModel(ExampleSet) - Method in class de.dfki.madm.mlwizard.Classifier
 

U

Util - Class in de.dfki.madm.mlwizard
 
Util() - Constructor for class de.dfki.madm.mlwizard.Util
 

V

var - Variable in class de.dfki.madm.mlwizard.metafeatures.AttributeStats
 

W

wizard(ExampleSet, KnowledgeBase, String, OutputStream) - Static method in class de.dfki.madm.mlwizard.cli.CommandLineInterface
 
WorstNodeLm - Class in de.dfki.madm.mlwizard.landmarking
This landmark learner is a DecisionStumpLearner, where a single decision node is chosen according to the smallest gain ratio.
WorstNodeLm(ExampleSet, Map<String, String>) - Constructor for class de.dfki.madm.mlwizard.landmarking.WorstNodeLm
 
write() - Method in class de.dfki.madm.mlwizard.KnowledgeBase
writes the knowledge base to the file (used within a stand-alone application)
write(String, IOObject) - Static method in class de.dfki.madm.mlwizard.Util
 
writeToRepository(IOObject, String) - Static method in class de.dfki.madm.mlwizard.Util
 

X

xValidation(ExampleSet, Operator, Map<String, String>) - Method in class de.dfki.madm.mlwizard.landmarking.AbstractLandmarker
An XValidation is applied on the Operator learner.

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