, 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] |
| loadFeatureSelectionFile() (defined in Data) | Data | |
| loadMetaWeights(int cross) (defined in PolynomialRegression) | PolynomialRegression | [virtual] |
| loadNormalization(int nCascade=0) | Data | |
| loadWeights(int cross) | PolynomialRegression | [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_enableCrossInteractions (defined in PolynomialRegression) | PolynomialRegression | [private] |
| 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_inputDim (defined in PolynomialRegression) | PolynomialRegression | [private] |
| 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_polyMean (defined in PolynomialRegression) | PolynomialRegression | [private] |
| m_polyOrder (defined in PolynomialRegression) | PolynomialRegression | [private] |
| m_polyStd (defined in PolynomialRegression) | PolynomialRegression | [private] |
| 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 PolynomialRegression) | PolynomialRegression | [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_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 PolynomialRegression) | PolynomialRegression | [private] |
| makeBinaryDataset() | Data | |
| mergeTrainAndTest() | Data | |
| mixDataset() | Data | |
| modelInit() | PolynomialRegression | [virtual] |
| modelUpdate(REAL *input, REAL *target, uint nSamples, uint crossRun) | PolynomialRegression | [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] |
| PolynomialRegression() | PolynomialRegression | |
| power(REAL x, int e) | PolynomialRegression | [private] |
| predictAllOutputs(REAL *rawInputs, REAL *outputs, uint nSamples, uint crossRun) | PolynomialRegression | [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() | PolynomialRegression | [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) | PolynomialRegression | [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 PolynomialRegression) | PolynomialRegression | [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) | PolynomialRegression | [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 | |
| ~PolynomialRegression() | PolynomialRegression | |
| ~StandardAlgorithm() | StandardAlgorithm | |
