public class GMLVQ extends AbstractClassifier implements TechnicalInformationHandler, Observer
GMLVQCore
to weka's data structure, input options as
well as its GUI integrationGMLVQCore
for details on GMLVQ's implementationModifier and Type | Class and Description |
---|---|
static interface |
GMLVQ.AlgorithmSettings
The interface provides all default values and options essential for the
algorithm.
|
static interface |
GMLVQ.CostFunctionsSettings
The interface provides all the cost function related settings.
|
static interface |
GMLVQ.MethodSettings
The interface provides all default values and options essential for the
method in general.
|
BATCH_SIZE_DEFAULT, NUM_DECIMAL_PLACES_DEFAULT
Constructor and Description |
---|
GMLVQ() |
batchSizeTipText, debugTipText, distributionsForInstances, doNotCheckCapabilitiesTipText, forName, getBatchSize, getDebug, getDoNotCheckCapabilities, getNumDecimalPlaces, getRevision, implementsMoreEfficientBatchPrediction, makeCopies, makeCopy, numDecimalPlacesTipText, postExecution, preExecution, run, runClassifier, setBatchSize, setDebug, setDoNotCheckCapabilities, setNumDecimalPlaces
public void buildClassifier(Instances trainingData) throws java.lang.Exception
buildClassifier
in interface Classifier
java.lang.Exception
public double classifyInstance(Instance instance)
classifyInstance
in interface Classifier
classifyInstance
in class AbstractClassifier
public double[] distributionForInstance(Instance instance)
distributionForInstance
in interface Classifier
distributionForInstance
in class AbstractClassifier
public Capabilities getCapabilities()
getCapabilities
in interface Classifier
getCapabilities
in interface CapabilitiesHandler
getCapabilities
in class AbstractClassifier
public SelectedTag get_1_costFunctionToOptimize()
public double get_2_costFunctionBeta()
public int getDataDimension()
public double get_2_dataPointRatioPerRound()
public int getNumberOfClasses()
public int get_1_numberOfEpochs()
public int get_1_numberOfPrototypesPerClass()
public int get_2_omegaDimension()
public double get_2_omegaLearningRate()
public java.lang.String[] getOptions()
getOptions
in interface OptionHandler
getOptions
in class AbstractClassifier
public double get_2_prototypeLearningRate()
public java.util.Map<java.lang.Double,java.lang.Integer> getPrototypesPerClass()
public java.lang.String get_2_sigmoidSigmaInterval()
public java.lang.String get_2_costFunctionWeights()
public TechnicalInformation getTechnicalInformation()
getTechnicalInformation
in interface TechnicalInformationHandler
public java.lang.String globalInfo()
public boolean is_2_matrixLearning()
public boolean is_2_parallelExecution()
public boolean is_1_visualization()
public boolean is_3_visualizeClassificationAccuracy()
public boolean is_3_visualizeWeightedAccuracy()
public boolean is_3_visualizeFMeasure()
public boolean is_3_visualizePrecisionRecall()
public boolean is_3_visualizeDefaultCost()
public static boolean isRelevanceLearning(Matrix omegaMatrix)
public java.util.Enumeration<Option> listOptions()
listOptions
in interface OptionHandler
listOptions
in class AbstractClassifier
public java.lang.String _2_matrixLearningTipText()
public java.lang.String _1_numberOfEpochsTipText()
public java.lang.String _1_numberOfPrototypesPerClassTipText()
public java.lang.String _2_omegaDimensionTipText()
public java.lang.String _2_omegaLearningRateTipText()
public java.lang.String _2_parallelExecutionTipText()
public java.lang.String _2_prototypeLearningRateTipText()
public java.lang.String _1_costFunctionToOptimizeTipText()
public java.lang.String _2_costFunctionBetaTipText()
public java.lang.String _2_costFunctionWeightsTipText()
public java.lang.String seedTipText()
public java.lang.String _2_sigmoidSigmaIntervalTipText()
public java.lang.String _1_visualizationTipText()
public java.lang.String _2_dataPointRatioPerRoundTipText()
public java.lang.String _3_visualizeClassificationAccuracyTipText()
public java.lang.String _3_visualizeWeightedAccuracyTipText()
public java.lang.String _3_visualizeFMeasureTipText()
public java.lang.String _3_visualizePrecisionRecallTipText()
public java.lang.String _3_visualizeDefaultCostTipText()
public void set_2_dataPointRatioPerRound(double dataPointRatioPerRound)
public void set_2_matrixLearning(boolean matrixLearning)
public void set_1_numberOfEpochs(int numberOfEpochs)
public void set_1_numberOfPrototypesPerClass(int numberOfPrototypesPerClass)
public void set_2_omegaDimension(int omegaDimension)
public void set_2_omegaLearningRate(double omegaLearningRate)
public void set_3_visualizeClassificationAccuracy(boolean visualize)
public void set_3_visualizeWeightedAccuracy(boolean visualize)
public void set_3_visualizeFMeasure(boolean visualize)
public void set_3_visualizePrecisionRecall(boolean visualize)
public void set_3_visualizeDefaultCost(boolean visualize)
public void set_1_costFunctionToOptimize(SelectedTag costFunctionToOptimizeTag)
public void setCostFunctionToOptimize(CostFunctionValue costFunctionValue)
public void addAdditionalCostFunction(CostFunctionValue costFunctionValue)
public void set_2_costFunctionBeta(double costFunctionBeta)
public void setOptions(java.lang.String[] options) throws java.lang.Exception
setOptions
in interface OptionHandler
setOptions
in class AbstractClassifier
java.lang.Exception
public void set_2_ParallelExecution(boolean parallelExecution)
public void set_2_prototypeLearningRate(double prototypeLearningRate)
public void set_2_sigmoidSigmaInterval(java.lang.String sigmoidSigmaIntervalString)
public void set_2_costFunctionWeights(java.lang.String costFunctionWeightsString)
public void set_1_visualization(boolean visualization)
public void updatePrototypes(java.util.List<Prototype> prototypes)
Observer
updatePrototypes
in interface Observer
public void updateCostFunctions(java.util.Map<CostFunctionValue,java.lang.Double> currentCostValues)
Observer
updateCostFunctions
in interface Observer
public void updateLambdaMatrix(Matrix lambdaMatrix)
Observer
updateLambdaMatrix
in interface Observer