NominalToBinary m_NominalToBinary
Filter m_Filter
int m_filterType
ReplaceMissingValues m_Missing
boolean m_checksTurnedOff
double m_delta
double m_deltaSquared
double m_Alin
double m_Blin
Kernel m_kernel
Kernel m_actualKernel
int m_NumTrain
double m_avg_target
no.uib.cipr.matrix.Matrix m_L
no.uib.cipr.matrix.Vector m_t
double[] m_weights
GMLVQCore.Builder builder
GMLVQCore gmlvqInstance
double[] m_Coefficients
boolean[] m_SelectedAttributes
Instances m_TransformedData
ReplaceMissingValues m_MissingFilter
NominalToBinary m_TransformFilter
double m_ClassStdDev
double m_ClassMean
int m_ClassIndex
double[] m_Means
double[] m_StdDevs
boolean m_outputAdditionalStats
int m_AttributeSelection
boolean m_EliminateColinearAttributes
boolean m_checksTurnedOff
double m_Ridge
boolean m_Minimal
boolean m_ModelBuilt
boolean m_isZeroR
int m_df
double m_RSquared
double m_RSquaredAdj
double m_FStat
double[] m_StdErrorOfCoef
double[] m_TStats
double[][] m_Par
double[][] m_Data
int m_NumPredictors
int m_ClassIndex
int m_NumClasses
double m_Ridge
RemoveUseless m_AttFilter
NominalToBinary m_NominalToBinary
ReplaceMissingValues m_ReplaceMissingValues
double m_LL
int m_MaxIts
boolean m_useConjugateGradientDescent
Instances m_structure
int m_numModels
Classifier m_ZeroR
boolean m_useDefaultModel
Instances m_instances
Instance m_currentInstance
boolean m_numeric
double[] m_attributeRanges
double[] m_attributeBases
MultilayerPerceptron.NeuralEnd[] m_outputs
MultilayerPerceptron.NeuralEnd[] m_inputs
NeuralConnection[] m_neuralNodes
int m_numClasses
int m_numAttributes
weka.classifiers.functions.MultilayerPerceptron.NodePanel m_nodePanel
weka.classifiers.functions.MultilayerPerceptron.ControlPanel m_controlPanel
int m_nextId
java.util.ArrayList<E> m_selected
int m_numEpochs
boolean m_stopIt
boolean m_stopped
boolean m_accepted
javax.swing.JFrame m_win
boolean m_autoBuild
boolean m_gui
int m_valSize
int m_driftThreshold
int m_randomSeed
java.util.Random m_random
boolean m_useNomToBin
NominalToBinary m_nominalToBinaryFilter
java.lang.String m_hiddenLayers
boolean m_normalizeAttributes
boolean m_decay
double m_learningRate
double m_momentum
int m_epoch
double m_error
boolean m_reset
boolean m_normalizeClass
SigmoidUnit m_sigmoidUnit
LinearUnit m_linearUnit
int m_link
boolean m_input
ReplaceMissingValues m_replaceMissing
Filter m_nominalToBinary
Normalize m_normalize
double m_lambda
double m_learningRate
double[] m_weights
double m_epsilon
double m_t
double m_numInstances
int m_epochs
boolean m_dontNormalize
boolean m_dontReplaceMissing
Instances m_data
int m_loss
int m_numModels
int m_periodicP
double m_minWordP
double m_minAbsCoefficient
boolean m_wordFrequencies
boolean m_normalize
double m_norm
double m_lnorm
java.util.LinkedHashMap<K,V> m_dictionary
StopwordsHandler m_StopwordsHandler
Tokenizer m_tokenizer
boolean m_lowercaseTokens
Stemmer m_stemmer
double m_lambda
double m_learningRate
double m_t
double m_bias
double m_numInstances
Instances m_data
int m_epochs
int m_loss
SGD m_svmProbs
boolean m_fitLogistic
Instances m_fitLogisticStructure
int m_numModels
double m_count
double m_weight
Attribute m_attribute
int m_attributeIndex
double m_slope
double m_intercept
double m_classMeanForMissing
boolean m_outputAdditionalStats
int m_df
double m_seSlope
double m_seIntercept
double m_tstatSlope
double m_tstatIntercept
double m_rsquared
double m_rsquaredAdj
double m_fstat
boolean m_suppressErrorMessage
LogisticBase m_boostedModel
NominalToBinary m_NominalToBinary
ReplaceMissingValues m_ReplaceMissingValues
int m_numBoostingIterations
int m_maxBoostingIterations
int m_heuristicStop
boolean m_useCrossValidation
boolean m_errorOnProbabilities
double m_weightTrimBeta
boolean m_useAIC
SMO.BinarySMO[][] m_classifiers
double m_C
double m_eps
double m_tol
int m_filterType
NominalToBinary m_NominalToBinary
Filter m_Filter
ReplaceMissingValues m_Missing
int m_classIndex
Attribute m_classAttribute
boolean m_KernelIsLinear
boolean m_checksTurnedOff
boolean m_fitCalibratorModels
Classifier m_calibrator
int m_numFolds
int m_randomSeed
Kernel m_kernel
double[] m_alpha
double m_b
double m_bLow
double m_bUp
int m_iLow
int m_iUp
Instances m_data
double[] m_weights
double[] m_sparseWeights
int[] m_sparseIndices
Kernel m_kernel
double[] m_class
double[] m_errors
SMOset m_I0
SMOset m_I1
SMOset m_I2
SMOset m_I3
SMOset m_I4
SMOset m_supportVectors
Classifier m_calibrator
Instances m_calibrationDataHeader
double m_sumOfWeights
long m_nEvals
int m_nCacheHits
int m_filterType
NominalToBinary m_NominalToBinary
Filter m_Filter
ReplaceMissingValues m_Missing
boolean m_onlyNumeric
double m_C
double m_x1
double m_x0
RegOptimizer m_optimizer
Kernel m_kernel
int m_MaxK
int m_NumIterations
double m_Exponent
int m_K
int[] m_Additions
boolean[] m_IsAddition
int[] m_Weights
Instances m_Train
int m_Seed
NominalToBinary m_NominalToBinary
ReplaceMissingValues m_ReplaceMissingValues
java.util.List<E> dataPoints
int numberOfTotalEpochs
int numberOfPrototypesPerClass
int omegaDimension
double learnRateChange
double prototypeLearningRate
double omegaLearningRate
double dataPointRatioPerRound
double sigmoidSigmaIntervalStart
double sigmoidSigmaIntervalEnd
double stopCriterion
boolean matrixLearning
boolean parallelExecution
boolean visualization
long seed
int numberOfClasses
int dataDimension
DataRandomizer dataRandomizer
OmegaMatrix omegaMatrix
OmegaMatrix lambdaMatrix
double lambdaMatrixScalingFactor
java.util.Map<K,V> prototypesPerClass
java.util.List<E> prototypes
SigmoidFunction sigmoidFunction
DefaultCostFunction costFunction
CostFunctionCalculator costFunctionCalculator
ClassificationErrorFunction classificationErrorFunction
UpdateManager updateManager
GradientDescent gradientDescent
java.util.List<E> additionalCostFunctions
java.util.List<E> dataPoints
int numberOfEpochs
int numberOfPrototypesPerClass
int omegaDimension
double learnRateChange
double dataPointRatioPerRound
double omegaLearningRate
double prototypeLearningRate
double sigmoidSigmaIntervalStart
double sigmoidSigmaIntervalEnd
double stopCriterion
boolean matrixLearning
boolean parallelExecution
boolean visualization
CostFunctionValue costFunctionToOptimize
java.util.List<E> additionalCostFunctions
double costFunctionBeta
double[] costFunctionWeights
long seed
int numberOfClasses
java.util.Map<K,V> prototypesPerClass
int dataDimension
DataRandomizer dataRandomizer
SigmoidFunction sigmoidFunction
CostFunctionCalculator costFunctionCalculator
double currentSigmoidSigma
double sigmoidSigmaIntervalStart
double sigmoidSigmaIntervalEnd
int totalNumberOfEpochs
java.util.List<E> dataPoints
java.util.List<E> prototypes
OmegaMatrix omegaMatrix
SigmoidFunction sigmoidFunction
DataRandomizer dataRandomizer
double currentCostValueToOptimize
double prototypeLearningRate
double omegaLearningRate
double learnRateChange
double stopCriterion
boolean relevanceLearning
int currentEpoch
int numberOfTotalEpochs
int numberOfPerformedPrototypeUpdates
int numberOfPerformedOmegaUpdates
double initialCostValueToOptimize
Matrix lambdaMatrix
double lambdaMatrixScalingFactor
CostFunctionCalculator costFunctionCalculator
java.util.Map<K,V> currentCostValues
SigmoidFunction sigmoidFunction
double truePositiveApprox
double trueNegativeApprox
double falsePositiveApprox
double falseNegativeApprox
SigmoidFunction sigmoidFunction
SigmoidFunction sigmoidFunction
CostFunctionValue costFunctionValueToOptimize
java.util.EnumSet<E extends java.lang.Enum<E>> additionalCostFunctionValuesToCalculate
ConfusionMatrix confusionMatrix
java.util.Map<K,V> persistentCostFunctions
double costFunctionBeta
double[] costFunctionWeights
java.util.Map<K,V> embeddedSpaceVectors
java.util.Map<K,V> winningInformation
OmegaMatrix omegaMatrix
double[] values
double classLabel
int dimension
long seed
java.util.Random random
int numberOfTrainingData
int fractionOfTrainingData
double ratio
float minimalValue
float maximalValue
float scalingFactor
float minimalHue
float saturation
float brightness
org.jfree.chart.JFreeChart chart
org.jfree.data.xy.XYSeriesCollection chartDataset
org.jfree.chart.renderer.xy.XYLineAndShapeRenderer chartRenderer
java.util.List<E> costFunctions
java.util.Map<K,V> costFunctionColors
VisualizerMouseAdapter mouseAdapter
org.jfree.chart.ChartPanel chartPanel
org.jfree.chart.JFreeChart chart
org.jfree.data.category.DefaultCategoryDataset chartTrainingData
java.util.List<E> chartPrototypeData
javax.swing.JList<E> listHideByClass
javax.swing.DefaultListModel<E> listModelHideByClass
javax.swing.JList<E> listShowByClass
javax.swing.DefaultListModel<E> listModelShowByClass
javax.swing.JList<E> listHideByAttribute
javax.swing.DefaultListModel<E> listModelHideByAttribute
javax.swing.JList<E> listShowByAttribute
javax.swing.DefaultListModel<E> listModelShowByAttribute
javax.swing.JList<E> listShowingPrototypes
javax.swing.DefaultListModel<E> listModelShowingPrototypes
javax.swing.JTree treePrototypes
java.util.Map<K,V> classColors
java.util.List<E> dataPoints
java.util.List<E> prototypes
java.util.Map<K,V> classNamesForDouble
java.lang.String[] attributeNames
int numberOfPrototypes
boolean prototypesInitialized
java.lang.String[] attributeNames
Matrix lambdaMatrix
java.util.SortedSet<E> featureImportance
javax.swing.table.DefaultTableModel tableModel
ColorScale colorScale
java.lang.String[] attributeNames
MatrixRenderer renderer
Matrix lambdaMatrix
java.text.DecimalFormat decimalFormat
int elementSize
int horizontalMargin
int verticalMargin
LambdaMatrixPanel parent
Matrix lambdaMatrix
ColorScale colorScale
boolean showScale
int matrixDrawWidth
int matrixDrawHeight
int matrixElementSize
int matrixMarginHorizontal
int matrixMarginVertical
int rowDimension
int columnDimension
java.text.DecimalFormat decimalFormat
java.util.Map<K,V> visualizations
java.util.concurrent.atomic.AtomicInteger counter
javax.swing.JToolBar toolbar
javax.swing.JTabbedPane tabbedPane
VisualizerMouseAdapter mouseAdapter
RunDetailsPanel runDetailsPanel
LambdaMatrixPanel panelLambdaMatrix
CostFunctionChartPanel panelCostFunctionChart
FeatureImpactPanel panelFeatureInfluence
FeatureAnalysisPanel panelFeatureAnalysis
ColorScale colorScale
javax.swing.JCheckBox checkBoxShowScale
javax.swing.JButton buttonExport