, including all inherited members.
  | addConstantInput() | Data |  | 
  | addDoubleParameter(double *param, string name, double min=-DBL_MAX, double max=DBL_MAX) | AutomaticParameterTuner |  | 
  | addEpochParameter(int *param, string name) | AutomaticParameterTuner |  | 
  | addIntegerParameter(int *param, string name, int min=INT_MIN, int max=INT_MAX) | AutomaticParameterTuner |  | 
  | Algorithm() | Algorithm |  | 
  | allocMemForCrossValidationSets() | Data |  | 
  | AUC() | AUC |  | 
  | AutomaticParameterTuner() | AutomaticParameterTuner |  | 
  | baggingRandomSeed(uint seed) | Data |  | 
  | calcCenter(const vector< pair< double, vector< double > > > &simplexPoints, vector< double > ¢er) | AutomaticParameterTuner |  [protected] | 
  | calcError(const vector< double > ¶mVector) | AutomaticParameterTuner |  [protected] | 
  | calcMinMax(const vector< pair< double, vector< double > > > &simplexPoints, int paramNr, double &min, double &max) | AutomaticParameterTuner |  [protected] | 
  | calcRMSEonBlend() | StandardAlgorithm |  [virtual] | 
  | calcRMSEonProbe() | StandardAlgorithm |  [virtual] | 
  | calculateFullPrediction() | StandardAlgorithm |  [protected] | 
  | clipValue(REAL input, REAL low, REAL high) | Algorithm |  | 
  | StandardAlgorithm::Algorithm::Framework::convertDateToInt(uint day, uint month, uint year, uint hour, uint minute, uint second) | Framework |  [static] | 
  | StandardAlgorithm::Algorithm::Data::convertDateToInt(uint day, uint month, uint year, uint hour, uint minute, uint second) | Framework |  [static] | 
  | StandardAlgorithm::AutomaticParameterTuner::convertDateToInt(uint day, uint month, uint year, uint hour, uint minute, uint second) | Framework |  [static] | 
  | StandardAlgorithm::AUC::convertDateToInt(uint day, uint month, uint year, uint hour, uint minute, uint second) | Framework |  [static] | 
  | StandardAlgorithm::Framework::convertDateToInt(uint day, uint month, uint year, uint hour, uint minute, uint second) | Framework |  [static] | 
  | Framework::convertDateToInt(uint day, uint month, uint year, uint hour, uint minute, uint second) | Framework |  [static] | 
  | StandardAlgorithm::Algorithm::Framework::convertIntToDate(uint date, uint &day, uint &month, uint &year, uint &hour, uint &minute, uint &second, uint &weekday) | Framework |  [static] | 
  | StandardAlgorithm::Algorithm::Data::convertIntToDate(uint date, uint &day, uint &month, uint &year, uint &hour, uint &minute, uint &second, uint &weekday) | Framework |  [static] | 
  | StandardAlgorithm::AutomaticParameterTuner::convertIntToDate(uint date, uint &day, uint &month, uint &year, uint &hour, uint &minute, uint &second, uint &weekday) | Framework |  [static] | 
  | StandardAlgorithm::AUC::convertIntToDate(uint date, uint &day, uint &month, uint &year, uint &hour, uint &minute, uint &second, uint &weekday) | Framework |  [static] | 
  | StandardAlgorithm::Framework::convertIntToDate(uint date, uint &day, uint &month, uint &year, uint &hour, uint &minute, uint &second, uint &weekday) | Framework |  [static] | 
  | Framework::convertIntToDate(uint date, uint &day, uint &month, uint &year, uint &hour, uint &minute, uint &second, uint &weekday) | Framework |  [static] | 
  | Data() | Data |  | 
  | deleteMemory() | Data |  | 
  | doBootstrapSampling(REAL *probs, REAL *&train, REAL *&target, REAL *&targetEff, REAL *&targetRes, int *&label, int nTrainNew=0) | Data |  | 
  | doFeatureSelection() | Data |  | 
  | enableBagging(bool en) | Data |  | 
  | expSearchChangeParams() | AutomaticParameterTuner |  | 
  | expSearchCheckErr(double error) | AutomaticParameterTuner |  | 
  | expSearcher(int minEpochs=0, int maxEpochs=200, int paramEpochs=3, int accelerationEpochs=2, double expInit=0.8, bool enableProbe=true, bool enableBlend=true) | AutomaticParameterTuner |  | 
  | expSearchGetLowestError() | AutomaticParameterTuner |  | 
  | expSearchParams(int minEpochs=0, int maxEpochs=100, int paramEpochs=3, int accelerationEpochs=10000, double expInit=0.8) | AutomaticParameterTuner |  | 
  | expSearchReinitStepSize() | AutomaticParameterTuner |  | 
  | expSearchSetEpochsToMinimizeBlend(int epochs) | AutomaticParameterTuner |  | 
  | extendTrainDataWithCascadeInputs() | Data |  | 
  | fillCascadeLearningInputs() | Data |  | 
  | fillNCrossValidationSet(int n) | Data |  | 
  | StandardAlgorithm::Algorithm::Framework::Framework() | Framework |  | 
  | StandardAlgorithm::Algorithm::Data::Framework() | Framework |  | 
  | StandardAlgorithm::AutomaticParameterTuner::Framework() | Framework |  | 
  | StandardAlgorithm::AUC::Framework() | Framework |  | 
  | StandardAlgorithm::Framework::Framework() | Framework |  | 
  | Framework::Framework() | Framework |  | 
  | freeNCrossValidationSet(int n) | Data |  | 
  | StandardAlgorithm::Algorithm::Framework::getAdditionalStartupParameter() | Framework |  [static] | 
  | StandardAlgorithm::Algorithm::Data::getAdditionalStartupParameter() | Framework |  [static] | 
  | StandardAlgorithm::AutomaticParameterTuner::getAdditionalStartupParameter() | Framework |  [static] | 
  | StandardAlgorithm::AUC::getAdditionalStartupParameter() | Framework |  [static] | 
  | StandardAlgorithm::Framework::getAdditionalStartupParameter() | Framework |  [static] | 
  | Framework::getAdditionalStartupParameter() | Framework |  [static] | 
  | getAUC(REAL *prediction, int *labels, int nClass, int nDomain, int nLines) | AUC |  | 
  | StandardAlgorithm::Algorithm::Framework::getDatasetType() | Framework |  [static] | 
  | StandardAlgorithm::Algorithm::Data::getDatasetType() | Framework |  [static] | 
  | StandardAlgorithm::AutomaticParameterTuner::getDatasetType() | Framework |  [static] | 
  | StandardAlgorithm::AUC::getDatasetType() | Framework |  [static] | 
  | StandardAlgorithm::Framework::getDatasetType() | Framework |  [static] | 
  | Framework::getDatasetType() | Framework |  [static] | 
  | getDirectoryFileList(string path) | Data |  [static] | 
  | StandardAlgorithm::Algorithm::Framework::getFrameworkMode() | Framework |  [static] | 
  | StandardAlgorithm::Algorithm::Data::getFrameworkMode() | Framework |  [static] | 
  | StandardAlgorithm::AutomaticParameterTuner::getFrameworkMode() | Framework |  [static] | 
  | StandardAlgorithm::AUC::getFrameworkMode() | Framework |  [static] | 
  | StandardAlgorithm::Framework::getFrameworkMode() | Framework |  [static] | 
  | Framework::getFrameworkMode() | Framework |  [static] | 
  | StandardAlgorithm::Algorithm::Framework::getMaxThreads() | Framework |  [static] | 
  | StandardAlgorithm::Algorithm::Data::getMaxThreads() | Framework |  [static] | 
  | StandardAlgorithm::AutomaticParameterTuner::getMaxThreads() | Framework |  [static] | 
  | StandardAlgorithm::AUC::getMaxThreads() | Framework |  [static] | 
  | StandardAlgorithm::Framework::getMaxThreads() | Framework |  [static] | 
  | Framework::getMaxThreads() | Framework |  [static] | 
  | StandardAlgorithm::Algorithm::Framework::getRandomSeed() | Framework |  [static] | 
  | StandardAlgorithm::Algorithm::Data::getRandomSeed() | Framework |  [static] | 
  | StandardAlgorithm::AutomaticParameterTuner::getRandomSeed() | Framework |  [static] | 
  | StandardAlgorithm::AUC::getRandomSeed() | Framework |  [static] | 
  | StandardAlgorithm::Framework::getRandomSeed() | Framework |  [static] | 
  | Framework::getRandomSeed() | Framework |  [static] | 
  | getReflectionPoint(const vector< double > ¢er, const vector< double > &worstPoint, vector< double > &reflectionPoint, double alpha) | AutomaticParameterTuner |  [protected] | 
  | init() | StandardAlgorithm |  [protected] | 
  | LinearModel() | LinearModel |  | 
  | loadFeatureSelectionFile() (defined in Data) | Data |  | 
  | loadMetaWeights(int cross) (defined in LinearModel) | LinearModel |  [virtual] | 
  | loadNormalization(int nCascade=0) | Data |  | 
  | loadWeights(int cross) | LinearModel |  [virtual] | 
  | m_addConstantInput (defined in Data) | Data |  [protected] | 
  | m_addOutputNoise (defined in Data) | Data |  [protected] | 
  | m_algorithmID (defined in Data) | Data |  [protected] | 
  | m_algorithmName (defined in Data) | Data |  [protected] | 
  | m_algorithmNameList (defined in Data) | Data |  [protected] | 
  | m_blendingAlgorithm (defined in Data) | Data |  [protected] | 
  | m_blendingEnableCrossValidation (defined in Data) | Data |  [protected] | 
  | m_blendingRegularization (defined in Data) | Data |  [protected] | 
  | m_blendStop (defined in StandardAlgorithm) | StandardAlgorithm |  [protected] | 
  | m_boolMap (defined in Data) | Data |  [protected] | 
  | m_cascadeInputs (defined in Data) | Data |  [protected] | 
  | m_crossIndex (defined in Data) | Data |  [protected] | 
  | m_crossValidationPrediction (defined in StandardAlgorithm) | StandardAlgorithm |  [protected] | 
  | m_dataPath (defined in Data) | Data |  [protected] | 
  | m_datasetName (defined in Data) | Data |  [protected] | 
  | m_datasetPath (defined in Data) | Data |  [protected] | 
  | m_dimensionalityReduction (defined in Data) | Data |  [protected] | 
  | m_disableTraining (defined in Data) | Data |  [protected] | 
  | m_disableWriteDscFile (defined in Data) | Data |  [protected] | 
  | m_doubleMap (defined in Data) | Data |  [protected] | 
  | m_doubleMax (defined in AutomaticParameterTuner) | AutomaticParameterTuner |  [protected] | 
  | m_doubleMin (defined in AutomaticParameterTuner) | AutomaticParameterTuner |  [protected] | 
  | m_doubleName (defined in AutomaticParameterTuner) | AutomaticParameterTuner |  [protected] | 
  | m_doubleParam (defined in AutomaticParameterTuner) | AutomaticParameterTuner |  [protected] | 
  | m_dscPath (defined in Data) | Data |  [protected] | 
  | m_enableBagging (defined in Data) | Data |  [protected] | 
  | m_enableCascadeLearning (defined in Data) | Data |  [protected] | 
  | m_enableClipping (defined in StandardAlgorithm) | StandardAlgorithm |  [protected] | 
  | m_enableDebug (defined in AutomaticParameterTuner) | AutomaticParameterTuner |  [protected] | 
  | m_enableFeatureSelection (defined in Data) | Data |  [protected] | 
  | m_enableGlobalBlendingWeights (defined in Data) | Data |  [protected] | 
  | m_enableGlobalMeanStdEstimate (defined in Data) | Data |  [protected] | 
  | m_enablePostBlendClipping (defined in Data) | Data |  [protected] | 
  | m_enablePostNNBlending (defined in Data) | Data |  [protected] | 
  | m_enableProbablisticNormalization (defined in Data) | Data |  [protected] | 
  | m_enableSaveMemory (defined in Data) | Data |  [protected] | 
  | m_enableStaticNormalization (defined in Data) | Data |  [protected] | 
  | m_enableTuneSwing (defined in StandardAlgorithm) | StandardAlgorithm |  [protected] | 
  | m_epochName (defined in AutomaticParameterTuner) | AutomaticParameterTuner |  [protected] | 
  | m_epochParam (defined in AutomaticParameterTuner) | AutomaticParameterTuner |  [protected] | 
  | m_epochParamBest (defined in AutomaticParameterTuner) | AutomaticParameterTuner |  [protected] | 
  | m_epochParamBreak (defined in AutomaticParameterTuner) | AutomaticParameterTuner |  [protected] | 
  | m_epochParamPos (defined in AutomaticParameterTuner) | AutomaticParameterTuner |  [protected] | 
  | m_errorFunction (defined in Data) | Data |  [protected] | 
  | m_expInit (defined in AutomaticParameterTuner) | AutomaticParameterTuner |  [protected] | 
  | m_expSearchAcceleration (defined in AutomaticParameterTuner) | AutomaticParameterTuner |  [protected] | 
  | m_expSearchAccelerationEpoch (defined in AutomaticParameterTuner) | AutomaticParameterTuner |  [protected] | 
  | m_expSearchDoubleParamBest (defined in AutomaticParameterTuner) | AutomaticParameterTuner |  [protected] | 
  | m_expSearchDoubleParamPos (defined in AutomaticParameterTuner) | AutomaticParameterTuner |  [protected] | 
  | m_expSearchEpoch (defined in AutomaticParameterTuner) | AutomaticParameterTuner |  [protected] | 
  | m_expSearchErrorBest (defined in AutomaticParameterTuner) | AutomaticParameterTuner |  [protected] | 
  | m_expSearchExponent (defined in AutomaticParameterTuner) | AutomaticParameterTuner |  [protected] | 
  | m_expSearchIntParamBest (defined in AutomaticParameterTuner) | AutomaticParameterTuner |  [protected] | 
  | m_expSearchIntParamPos (defined in AutomaticParameterTuner) | AutomaticParameterTuner |  [protected] | 
  | m_expSearchMaxEpochs (defined in AutomaticParameterTuner) | AutomaticParameterTuner |  [protected] | 
  | m_expSearchMaxEpochsBlend (defined in AutomaticParameterTuner) | AutomaticParameterTuner |  [protected] | 
  | m_expSearchMinEpochs (defined in AutomaticParameterTuner) | AutomaticParameterTuner |  [protected] | 
  | m_expSearchParamAccelerationEpochs (defined in AutomaticParameterTuner) | AutomaticParameterTuner |  [protected] | 
  | m_expSearchParamDirection (defined in AutomaticParameterTuner) | AutomaticParameterTuner |  [protected] | 
  | m_expSearchParamEpochs (defined in AutomaticParameterTuner) | AutomaticParameterTuner |  [protected] | 
  | m_expSearchTime (defined in AutomaticParameterTuner) | AutomaticParameterTuner |  [protected] | 
  | m_expSearchVariationCnt (defined in AutomaticParameterTuner) | AutomaticParameterTuner |  [protected] | 
  | m_featureSelectionWriteBinaryDataset (defined in Data) | Data |  [protected] | 
  | m_fullPrediction (defined in StandardAlgorithm) | StandardAlgorithm |  [protected] | 
  | m_fullPredPath (defined in Data) | Data |  [protected] | 
  | m_globalTrainingLoops (defined in Data) | Data |  [protected] | 
  | m_initMaxSwing (defined in StandardAlgorithm) | StandardAlgorithm |  [protected] | 
  | m_inRetraining (defined in Algorithm) | Algorithm |  | 
  | m_intMap (defined in Data) | Data |  [protected] | 
  | m_intMax (defined in AutomaticParameterTuner) | AutomaticParameterTuner |  [protected] | 
  | m_intMin (defined in AutomaticParameterTuner) | AutomaticParameterTuner |  [protected] | 
  | m_intName (defined in AutomaticParameterTuner) | AutomaticParameterTuner |  [protected] | 
  | m_intParam (defined in AutomaticParameterTuner) | AutomaticParameterTuner |  [protected] | 
  | m_labelPrediction (defined in StandardAlgorithm) | StandardAlgorithm |  [protected] | 
  | m_loadWeightsBeforeTraining (defined in Data) | Data |  [protected] | 
  | m_maxSwing (defined in StandardAlgorithm) | StandardAlgorithm |  [protected] | 
  | m_maxThreadsInCross (defined in Data) | Data |  [protected] | 
  | m_maxTuninigEpochs (defined in StandardAlgorithm) | StandardAlgorithm |  [protected] | 
  | m_mean (defined in Data) | Data |  [protected] | 
  | m_minimzeBlend (defined in StandardAlgorithm) | StandardAlgorithm |  [protected] | 
  | m_minimzeBlendClassificationError (defined in StandardAlgorithm) | StandardAlgorithm |  [protected] | 
  | m_minimzeProbe (defined in StandardAlgorithm) | StandardAlgorithm |  [protected] | 
  | m_minimzeProbeClassificationError (defined in StandardAlgorithm) | StandardAlgorithm |  [protected] | 
  | m_minTuninigEpochs (defined in StandardAlgorithm) | StandardAlgorithm |  [protected] | 
  | m_mixDatasetIndices (defined in Data) | Data |  [protected] | 
  | m_mixList (defined in Data) | Data |  [protected] | 
  | m_nCascadeInputs (defined in Data) | Data |  [protected] | 
  | m_nClass (defined in Data) | Data |  [protected] | 
  | m_nCross (defined in Data) | Data |  [protected] | 
  | m_nDomain (defined in Data) | Data |  [protected] | 
  | m_negativeTarget (defined in Data) | Data |  [protected] | 
  | m_nFeatures (defined in Data) | Data |  [protected] | 
  | m_nMixDataset (defined in Data) | Data |  [protected] | 
  | m_nMixTrainList (defined in Data) | Data |  [protected] | 
  | m_nTest (defined in Data) | Data |  [protected] | 
  | m_nTrain (defined in Data) | Data |  [protected] | 
  | m_optimizeBlendRMSE (defined in AutomaticParameterTuner) | AutomaticParameterTuner |  [protected] | 
  | m_optimizeProbeRMSE (defined in AutomaticParameterTuner) | AutomaticParameterTuner |  [protected] | 
  | m_outOfBagEstimate (defined in StandardAlgorithm) | StandardAlgorithm |  [protected] | 
  | m_outOfBagEstimateCnt (defined in StandardAlgorithm) | StandardAlgorithm |  [protected] | 
  | m_positiveTarget (defined in Data) | Data |  [protected] | 
  | m_prediction (defined in StandardAlgorithm) | StandardAlgorithm |  [protected] | 
  | m_predictionBest (defined in StandardAlgorithm) | StandardAlgorithm |  [protected] | 
  | m_predictionProbe (defined in StandardAlgorithm) | StandardAlgorithm |  [protected] | 
  | m_probe (defined in Data) | Data |  [protected] | 
  | m_probeIndex (defined in Data) | Data |  [protected] | 
  | m_probeLabel (defined in Data) | Data |  [protected] | 
  | m_probeSize (defined in Data) | Data |  [protected] | 
  | m_probeTarget (defined in Data) | Data |  [protected] | 
  | m_probeTargetEffect (defined in Data) | Data |  [protected] | 
  | m_probeTargetResidual (defined in Data) | Data |  [protected] | 
  | m_randomSeedBagging (defined in Data) | Data |  [protected] | 
  | m_randSeed (defined in Data) | Data |  [protected] | 
  | m_reg (defined in LinearModel) | LinearModel |  [private] | 
  | m_ridgeModifiers (defined in LinearModel) | LinearModel |  [private] | 
  | m_singlePrediction (defined in StandardAlgorithm) | StandardAlgorithm |  [protected] | 
  | m_slotBoundaries (defined in Data) | Data |  [protected] | 
  | m_standardDeviationMin (defined in Data) | Data |  [protected] | 
  | m_staticMeanNormalization (defined in Data) | Data |  [protected] | 
  | m_staticStdNormalization (defined in Data) | Data |  [protected] | 
  | m_std (defined in Data) | Data |  [protected] | 
  | m_stringMap (defined in Data) | Data |  [protected] | 
  | m_subsampleFeatures (defined in Data) | Data |  [protected] | 
  | m_subsampleTrainSet (defined in Data) | Data |  [protected] | 
  | m_support (defined in Data) | Data |  [protected] | 
  | m_targetMean (defined in Data) | Data |  [protected] | 
  | m_tempPath (defined in Data) | Data |  [protected] | 
  | m_testLabelOrig (defined in Data) | Data |  [protected] | 
  | m_testOrig (defined in Data) | Data |  [protected] | 
  | m_testTargetOrig (defined in Data) | Data |  [protected] | 
  | m_train (defined in Data) | Data |  [protected] | 
  | m_trainBaggingIndex (defined in Data) | Data |  [protected] | 
  | m_trainLabel (defined in Data) | Data |  [protected] | 
  | m_trainLabelOrig (defined in Data) | Data |  [protected] | 
  | m_trainOnFullPredictorFile (defined in Data) | Data |  [protected] | 
  | m_trainOrig (defined in Data) | Data |  [protected] | 
  | m_trainSize (defined in Data) | Data |  [protected] | 
  | m_trainTarget (defined in Data) | Data |  [protected] | 
  | m_trainTargetEffect (defined in Data) | Data |  [protected] | 
  | m_trainTargetOrig (defined in Data) | Data |  [protected] | 
  | m_trainTargetOrigEffect (defined in Data) | Data |  [protected] | 
  | m_trainTargetOrigResidual (defined in Data) | Data |  [protected] | 
  | m_trainTargetResidual (defined in Data) | Data |  [protected] | 
  | m_tuneRigeModifiers (defined in LinearModel) | LinearModel |  [private] | 
  | m_valid (defined in Data) | Data |  [protected] | 
  | m_validationType (defined in Data) | Data |  [protected] | 
  | m_validLabel (defined in Data) | Data |  [protected] | 
  | m_validSize (defined in Data) | Data |  [protected] | 
  | m_validTarget (defined in Data) | Data |  [protected] | 
  | m_weightFile (defined in StandardAlgorithm) | StandardAlgorithm |  [protected] | 
  | m_wrongLabelCnt (defined in StandardAlgorithm) | StandardAlgorithm |  [protected] | 
  | m_x (defined in LinearModel) | LinearModel |  [private] | 
  | makeBinaryDataset() | Data |  | 
  | mergeTrainAndTest() | Data |  | 
  | mixDataset() | Data |  | 
  | modelInit() | LinearModel |  [virtual] | 
  | modelUpdate(REAL *input, REAL *target, uint nSamples, uint crossRun) | LinearModel |  [virtual] | 
  | NelderMeadSearch(int maxEpochs=200) | AutomaticParameterTuner |  | 
  | normalizeZeroOne() | Data |  | 
  | paramDoubleNames (defined in StandardAlgorithm) | StandardAlgorithm |  [protected] | 
  | paramDoubleValues (defined in StandardAlgorithm) | StandardAlgorithm |  [protected] | 
  | paramEpochNames (defined in StandardAlgorithm) | StandardAlgorithm |  [protected] | 
  | paramEpochValues (defined in StandardAlgorithm) | StandardAlgorithm |  [protected] | 
  | paramIntNames (defined in StandardAlgorithm) | StandardAlgorithm |  [protected] | 
  | paramIntValues (defined in StandardAlgorithm) | StandardAlgorithm |  [protected] | 
  | partitionDatasetToCrossValidationSets() | Data |  | 
  | plotParameters(int epoch, const vector< pair< double, vector< double > > > &simplexPoints) | AutomaticParameterTuner |  [protected] | 
  | predictAllOutputs(REAL *rawInputs, REAL *outputs, uint nSamples, uint crossRun) | LinearModel |  [virtual] | 
  | predictMultipleOutputs(REAL *rawInput, REAL *effect, REAL *output, int *label, int nSamples, int crossRun) | StandardAlgorithm |  [virtual] | 
  | readDataset(string name) | Data |  | 
  | readDscFile(string name) | Data |  | 
  | readEffectFile() | Data |  | 
  | readMaps() | StandardAlgorithm |  [protected] | 
  | readParameter(string line, int mode) | Data |  | 
  | readSpecificMaps() | LinearModel |  [virtual] | 
  | reduceFeatureSize(REAL *&table, int tableRows, int &tableCols, REAL percent, bool loadColumnSet) | Data |  | 
  | reduceTrainingSetSize(REAL percent) | Data |  | 
  | removeDoubleParameter(string name) | AutomaticParameterTuner |  | 
  | removeEpochParameter(string name) | AutomaticParameterTuner |  | 
  | removeIntegerParameter(string name) | AutomaticParameterTuner |  | 
  | saveBestPrediction() | StandardAlgorithm |  [virtual] | 
  | saveFeatureSelectionFile() (defined in Data) | Data |  | 
  | saveWeights(int cross) | LinearModel |  [virtual] | 
  | StandardAlgorithm::Algorithm::Framework::setAdditionalStartupParameter(char *s) | Framework |  [static] | 
  | StandardAlgorithm::Algorithm::Data::setAdditionalStartupParameter(char *s) | Framework |  [static] | 
  | StandardAlgorithm::AutomaticParameterTuner::setAdditionalStartupParameter(char *s) | Framework |  [static] | 
  | StandardAlgorithm::AUC::setAdditionalStartupParameter(char *s) | Framework |  [static] | 
  | StandardAlgorithm::Framework::setAdditionalStartupParameter(char *s) | Framework |  [static] | 
  | Framework::setAdditionalStartupParameter(char *s) | Framework |  [static] | 
  | setAlgorithmList(vector< string > m_algorithmNameList) | Data |  | 
  | setCurrentParameter(const vector< double > ¶mVector) | AutomaticParameterTuner |  [protected] | 
  | setDataPointers(Data *data) | Data |  | 
  | StandardAlgorithm::Algorithm::Framework::setDatasetType(bool isClassification) | Framework |  [static] | 
  | StandardAlgorithm::Algorithm::Data::setDatasetType(bool isClassification) | Framework |  [static] | 
  | StandardAlgorithm::AutomaticParameterTuner::setDatasetType(bool isClassification) | Framework |  [static] | 
  | StandardAlgorithm::AUC::setDatasetType(bool isClassification) | Framework |  [static] | 
  | StandardAlgorithm::Framework::setDatasetType(bool isClassification) | Framework |  [static] | 
  | Framework::setDatasetType(bool isClassification) | Framework |  [static] | 
  | setDebug(bool en) | AutomaticParameterTuner |  | 
  | StandardAlgorithm::Algorithm::Framework::setFrameworkMode(int mode) | Framework |  [static] | 
  | StandardAlgorithm::Algorithm::Data::setFrameworkMode(int mode) | Framework |  [static] | 
  | StandardAlgorithm::AutomaticParameterTuner::setFrameworkMode(int mode) | Framework |  [static] | 
  | StandardAlgorithm::AUC::setFrameworkMode(int mode) | Framework |  [static] | 
  | StandardAlgorithm::Framework::setFrameworkMode(int mode) | Framework |  [static] | 
  | Framework::setFrameworkMode(int mode) | Framework |  [static] | 
  | StandardAlgorithm::Algorithm::Framework::setMaxThreads(int n) | Framework |  [static] | 
  | StandardAlgorithm::Algorithm::Data::setMaxThreads(int n) | Framework |  [static] | 
  | StandardAlgorithm::AutomaticParameterTuner::setMaxThreads(int n) | Framework |  [static] | 
  | StandardAlgorithm::AUC::setMaxThreads(int n) | Framework |  [static] | 
  | StandardAlgorithm::Framework::setMaxThreads(int n) | Framework |  [static] | 
  | Framework::setMaxThreads(int n) | Framework |  [static] | 
  | setOptimizeBlendRmse(bool enable) | AutomaticParameterTuner |  | 
  | setOptimizeProbeRmse(bool enable) | AutomaticParameterTuner |  | 
  | setPathes(string temp, string dsc, string fullPred, string data) | Data |  | 
  | setPredictionMode(int cross) | StandardAlgorithm |  [virtual] | 
  | StandardAlgorithm::Algorithm::Framework::setRandomSeed(int n) | Framework |  [static] | 
  | StandardAlgorithm::Algorithm::Data::setRandomSeed(int n) | Framework |  [static] | 
  | StandardAlgorithm::AutomaticParameterTuner::setRandomSeed(int n) | Framework |  [static] | 
  | StandardAlgorithm::AUC::setRandomSeed(int n) | Framework |  [static] | 
  | StandardAlgorithm::Framework::setRandomSeed(int n) | Framework |  [static] | 
  | Framework::setRandomSeed(int n) | Framework |  [static] | 
  | simpleStochasticParameterFinder(double minProbeImpro=0.00002, int maxProbeEpochsWithoutImpro=100, double minBlendImpro=0.000001, int maxBlendEpochsWithoutImpro=200, double stdDev=0.1) | AutomaticParameterTuner |  | 
  | solver (defined in LinearModel) | LinearModel |  [private] | 
  | splitStringToIntegerList(string str, char delimiter) | Data |  [static] | 
  | splitStringToStringList(string str, char delimiter) | Data |  [static] | 
  | StandardAlgorithm() | StandardAlgorithm |  | 
  | templateGenerator(int id, string preEffect, int nameID, bool blendStop) | LinearModel |  [static] | 
  | train() | StandardAlgorithm |  [virtual] | 
  | vectorSampling(REAL *probs, int length) | Data |  | 
  | writeFullPrediction(int nSamples) | StandardAlgorithm |  [protected] | 
  | ~Algorithm() | Algorithm |  [virtual] | 
  | ~AUC() | AUC |  | 
  | ~AutomaticParameterTuner() | AutomaticParameterTuner |  [virtual] | 
  | ~Data() | Data |  [virtual] | 
  | StandardAlgorithm::Algorithm::Framework::~Framework() | Framework |  | 
  | StandardAlgorithm::Algorithm::Data::~Framework() | Framework |  | 
  | StandardAlgorithm::AutomaticParameterTuner::~Framework() | Framework |  | 
  | StandardAlgorithm::AUC::~Framework() | Framework |  | 
  | StandardAlgorithm::Framework::~Framework() | Framework |  | 
  | Framework::~Framework() | Framework |  | 
  | ~LinearModel() | LinearModel |  | 
  | ~StandardAlgorithm() | StandardAlgorithm |  |