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CDenseLabels Class Reference

Detailed Description

Dense integer or floating point labels.

DenseLabels here are always real-valued and thus applicable to classification (cf. CClassifier) and regression (cf. CRegression) problems.

This class implements the shared functions for storing, and accessing label (vectors).

Definition at line 35 of file DenseLabels.h.

Inheritance diagram for CDenseLabels:
Inheritance graph
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Public Member Functions

 CDenseLabels ()
 CDenseLabels (int32_t num_labels)
 CDenseLabels (CFile *loader)
virtual ~CDenseLabels ()
virtual void ensure_valid (const char *context=NULL)
virtual void load (CFile *loader)
virtual void save (CFile *writer)
bool set_label (int32_t idx, float64_t label)
bool set_int_label (int32_t idx, int32_t label)
float64_t get_label (int32_t idx)
int32_t get_int_label (int32_t idx)
SGVector< float64_tget_labels ()
SGVector< float64_tget_labels_copy ()
void set_labels (SGVector< float64_t > v)
void set_to_one ()
void zero ()
void set_to_const (float64_t c)
SGVector< int32_t > get_int_labels ()
void set_int_labels (SGVector< int32_t > labels)
void set_int_labels (SGVector< int64_t > labels)
virtual int32_t get_num_labels () const
virtual ELabelType get_label_type () const =0
virtual void add_subset (SGVector< index_t > subset)
virtual void add_subset_in_place (SGVector< index_t > subset)
virtual void remove_subset ()
virtual void remove_all_subsets ()
virtual void set_value (float64_t value, int32_t idx)
virtual float64_t get_value (int32_t idx)
virtual void set_values (SGVector< float64_t > values)
virtual SGVector< float64_tget_values ()
virtual CSGObjectshallow_copy () const
virtual CSGObjectdeep_copy () const
virtual const char * get_name () const =0
virtual bool is_generic (EPrimitiveType *generic) const
template<class T >
void set_generic ()
void unset_generic ()
virtual void print_serializable (const char *prefix="")
virtual bool save_serializable (CSerializableFile *file, const char *prefix="", int32_t param_version=Version::get_version_parameter())
virtual bool load_serializable (CSerializableFile *file, const char *prefix="", int32_t param_version=Version::get_version_parameter())
DynArray< TParameter * > * load_file_parameters (const SGParamInfo *param_info, int32_t file_version, CSerializableFile *file, const char *prefix="")
DynArray< TParameter * > * load_all_file_parameters (int32_t file_version, int32_t current_version, CSerializableFile *file, const char *prefix="")
void map_parameters (DynArray< TParameter * > *param_base, int32_t &base_version, DynArray< const SGParamInfo * > *target_param_infos)
void set_global_io (SGIO *io)
SGIOget_global_io ()
void set_global_parallel (Parallel *parallel)
Parallelget_global_parallel ()
void set_global_version (Version *version)
Versionget_global_version ()
SGStringList< char > get_modelsel_names ()
void print_modsel_params ()
char * get_modsel_param_descr (const char *param_name)
index_t get_modsel_param_index (const char *param_name)
void build_gradient_parameter_dictionary (CMap< TParameter *, CSGObject * > *dict)
virtual void update_parameter_hash ()
virtual bool parameter_hash_changed ()
virtual bool equals (CSGObject *other, float64_t accuracy=0.0, bool tolerant=false)
virtual CSGObjectclone ()

Public Attributes

SGIOio
Parallelparallel
Versionversion
Parameterm_parameters
Parameterm_model_selection_parameters
Parameterm_gradient_parameters
ParameterMapm_parameter_map
uint32_t m_hash

Static Public Attributes

static const int32_t REJECTION_LABEL = -2

Protected Member Functions

virtual TParametermigrate (DynArray< TParameter * > *param_base, const SGParamInfo *target)
virtual void one_to_one_migration_prepare (DynArray< TParameter * > *param_base, const SGParamInfo *target, TParameter *&replacement, TParameter *&to_migrate, char *old_name=NULL)
virtual void load_serializable_pre () throw (ShogunException)
virtual void load_serializable_post () throw (ShogunException)
virtual void save_serializable_pre () throw (ShogunException)
virtual void save_serializable_post () throw (ShogunException)

Protected Attributes

SGVector< float64_tm_labels
CSubsetStackm_subset_stack
SGVector< float64_tm_current_values

Constructor & Destructor Documentation

default constructor

Definition at line 23 of file DenseLabels.cpp.

CDenseLabels ( int32_t  num_labels)

constructor

Parameters
num_labelsnumber of labels

Definition at line 29 of file DenseLabels.cpp.

CDenseLabels ( CFile loader)

constructor

Parameters
loaderFile object via which to load data

Definition at line 37 of file DenseLabels.cpp.

~CDenseLabels ( )
virtual

destructor

Definition at line 44 of file DenseLabels.cpp.

Member Function Documentation

void add_subset ( SGVector< index_t subset)
virtualinherited

Adds a subset of indices on top of the current subsets (possibly subset of subset). Every call causes a new active index vector to be stored. Added subsets can be removed one-by-one. If this is not needed, add_subset_in_place() should be used (does not store intermediate index vectors)

Parameters
subsetsubset of indices to add

Definition at line 39 of file Labels.cpp.

void add_subset_in_place ( SGVector< index_t subset)
virtualinherited

Sets/changes latest added subset. This allows to add multiple subsets with in-place memory requirements. They cannot be removed one-by-one afterwards, only the latest active can. If this is needed, use add_subset(). If no subset is active, this just adds.

Parameters
subsetsubset of indices to replace the latest one with.

Definition at line 44 of file Labels.cpp.

void build_gradient_parameter_dictionary ( CMap< TParameter *, CSGObject * > *  dict)
inherited

Builds a dictionary of all parameters in SGObject as well of those of SGObjects that are parameters of this object. Dictionary maps parameters to the objects that own them.

Parameters
dictdictionary of parameters to be built.

Definition at line 1185 of file SGObject.cpp.

CSGObject * clone ( )
virtualinherited

Creates a clone of the current object. This is done via recursively traversing all parameters, which corresponds to a deep copy. Calling equals on the cloned object always returns true although none of the memory of both objects overlaps.

Returns
an identical copy of the given object, which is disjoint in memory. NULL if the clone fails. Note that the returned object is SG_REF'ed

Definition at line 1302 of file SGObject.cpp.

CSGObject * deep_copy ( ) const
virtualinherited

A deep copy. All the instance variables will also be copied.

Definition at line 146 of file SGObject.cpp.

void ensure_valid ( const char *  context = NULL)
virtual

Make sure the label is valid, otherwise raise SG_ERROR.

possible with subset

Parameters
contextoptional message to convey the context

Implements CLabels.

Reimplemented in CBinaryLabels, and CMulticlassLabels.

Definition at line 139 of file DenseLabels.cpp.

bool equals ( CSGObject other,
float64_t  accuracy = 0.0,
bool  tolerant = false 
)
virtualinherited

Recursively compares the current SGObject to another one. Compares all registered numerical parameters, recursion upon complex (SGObject) parameters. Does not compare pointers!

May be overwritten but please do with care! Should not be necessary in most cases.

Parameters
otherobject to compare with
accuracyaccuracy to use for comparison (optional)
tolerantallows linient check on float equality (within accuracy)
Returns
true if all parameters were equal, false if not

Definition at line 1206 of file SGObject.cpp.

SGIO * get_global_io ( )
inherited

get the io object

Returns
io object

Definition at line 183 of file SGObject.cpp.

Parallel * get_global_parallel ( )
inherited

get the parallel object

Returns
parallel object

Definition at line 224 of file SGObject.cpp.

Version * get_global_version ( )
inherited

get the version object

Returns
version object

Definition at line 237 of file SGObject.cpp.

int32_t get_int_label ( int32_t  idx)

get INT label

possible with subset

Parameters
idxindex of label to get
Returns
INT value of label

Definition at line 191 of file DenseLabels.cpp.

SGVector< int32_t > get_int_labels ( )

get INT label vector

possible with subset

Returns
INT labels

Definition at line 105 of file DenseLabels.cpp.

float64_t get_label ( int32_t  idx)

get label

possible with subset

Parameters
idxindex of label to get
Returns
value of label

Definition at line 184 of file DenseLabels.cpp.

virtual ELabelType get_label_type ( ) const
pure virtual

get label type

Returns
label type (binary, multiclass, ...)

Implements CLabels.

Implemented in CBinaryLabels, CMulticlassLabels, and CRegressionLabels.

SGVector< float64_t > get_labels ( )

Getter for labels

Returns
labels, a copy if a subset is set

Definition at line 82 of file DenseLabels.cpp.

SGVector< float64_t > get_labels_copy ( )

get copy of labels.

possible with subset

Returns
labels

Definition at line 90 of file DenseLabels.cpp.

SGStringList< char > get_modelsel_names ( )
inherited
Returns
vector of names of all parameters which are registered for model selection

Definition at line 1077 of file SGObject.cpp.

char * get_modsel_param_descr ( const char *  param_name)
inherited

Returns description of a given parameter string, if it exists. SG_ERROR otherwise

Parameters
param_namename of the parameter
Returns
description of the parameter

Definition at line 1101 of file SGObject.cpp.

index_t get_modsel_param_index ( const char *  param_name)
inherited

Returns index of model selection parameter with provided index

Parameters
param_namename of model selection parameter
Returns
index of model selection parameter with provided name, -1 if there is no such

Definition at line 1114 of file SGObject.cpp.

virtual const char* get_name ( ) const
pure virtualinherited

Returns the name of the SGSerializable instance. It MUST BE the CLASS NAME without the prefixed `C'.

Returns
name of the SGSerializable

Implements SGRefObject.

Implemented in CMath, CHMM, CStringFeatures< ST >, CStringFeatures< T >, CStringFeatures< uint8_t >, CStringFeatures< char >, CStringFeatures< uint16_t >, CSVMLight, CTrie< Trie >, CTrie< DNATrie >, CTrie< POIMTrie >, CDynamicArray< T >, CDynamicArray< float64_t >, CDynamicArray< float32_t >, CDynamicArray< int32_t >, CDynamicArray< char >, CDynamicArray< bool >, CMultitaskKernelTreeNormalizer, CList, CDynProg, CLibSVMFile, CDenseFeatures< ST >, CDenseFeatures< uint32_t >, CDenseFeatures< float64_t >, CDenseFeatures< T >, CDenseFeatures< uint16_t >, CFile, CStatistics, CSparseFeatures< ST >, CSparseFeatures< float64_t >, CSparseFeatures< T >, CSpecificityMeasure, CPrecisionMeasure, CPlif, CRecallMeasure, CUAIFile, CDynamicObjectArray, CCrossCorrelationMeasure, CCSVFile, CF1Measure, CLaRank, CBinaryFile, CWRACCMeasure, CProtobufFile, CRBM, CTaxonomy, CBALMeasure, CBitString, CStreamingVwFeatures, CStreamingSparseFeatures< T >, CMultitaskKernelPlifNormalizer, CErrorRateMeasure, CWDSVMOcas, CMachine, CNeuralLayer, CAccuracyMeasure, CStreamingFile, CQuadraticTimeMMD, CRandom, CStreamingMMD, CMultitaskKernelMaskNormalizer, CMemoryMappedFile< T >, CMemoryMappedFile< ST >, CAlphabet, CMKL, CStreamingDenseFeatures< T >, CLMNNStatistics, CStructuredModel, CStreamingDenseFeatures< float64_t >, CStreamingDenseFeatures< float32_t >, CCombinedDotFeatures, CFeatureSelection< ST >, CFeatureSelection< float64_t >, CGUIStructure, CCache< T >, CCache< SGSparseVectorEntry< ST > >, CCache< uint32_t >, CCache< ST >, CCache< SGSparseVectorEntry< float64_t > >, CCache< float64_t >, CCache< uint8_t >, CCache< KERNELCACHE_ELEM >, CCache< char >, CCache< uint16_t >, CCache< SGSparseVectorEntry< T > >, CMultitaskKernelMaskPairNormalizer, CSVM, CMultitaskKernelNormalizer, CNeuralNetwork, CGUIClassifier, CGaussian, CGUIFeatures, CGMM, CBinaryStream< T >, CHashedWDFeaturesTransposed, CLinearHMM, CSimpleFile< T >, CParameterCombination, CDeepBeliefNetwork, CStreamingStringFeatures< T >, CNeuralLinearLayer, CMulticlassSVM, CStateModel, CRandomKitchenSinksDotFeatures, COnlineLinearMachine, CVwParser, CPluginEstimate, CVowpalWabbit, CBinnedDotFeatures, CSVMOcas, CNeuralConvolutionalLayer, CSVRLight, CHashedWDFeatures, CPlifMatrix, CCrossValidation, CImplicitWeightedSpecFeatures, CCombinedFeatures, CSparseMatrixOperator< T >, CSNPFeatures, CWDFeatures, CCrossValidationMulticlassStorage, CHashedDenseFeatures< ST >, CIOBuffer, CLossFunction, CTwoStateModel, CPCA, CHMSVMModel, CKMeans, CDeepAutoencoder, CLeastAngleRegression, CGUIKernel, CKNN, CRandomFourierGaussPreproc, CMKLMulticlass, CHashedSparseFeatures< ST >, CAutoencoder, CHypothesisTest, CExplicitSpecFeatures, CModelSelectionParameters, CLibLinearMTL, CNOCCO, CPositionalPWM, CHashedDocDotFeatures, CGUIHMM, COnlineSVMSGD, CIntegration, CJacobiEllipticFunctions, CLibLinear, CLDA, CZeroMeanCenterKernelNormalizer, CSparsePolyFeatures, CHashedMultilabelModel, CSqrtDiagKernelNormalizer, CHuberLoss, CScatterKernelNormalizer, CCplex, CFisherLDA, CHSIC, CRationalApproximation, CStochasticProximityEmbedding, CLatentModel, CGMNPLib, CMulticlassMachine, CDixonQTestRejectionStrategy, CTableFactorType, CSVMSGD, CVwCacheReader, CLBPPyrDotFeatures, CRidgeKernelNormalizer, CDependenceMaximization, CLinearMachine, CMulticlassSOLabels, CSerializableAsciiFile, CSGDQN, CSNPStringKernel, CTime, CMatrixFeatures< ST >, CWeightedCommWordStringKernel, CHingeLoss, CTwoSampleTest, CSquaredLoss, CAbsoluteDeviationLoss, CExponentialLoss, CQPBSVMLib, CCustomKernel, CMulticlassLabels, CHash, CLinearTimeMMD, CFactor, CPlifArray, CStreamingVwFile, CGraphCut, CStreamingHashedDocDotFeatures, CKernelIndependenceTest, CCustomDistance, CWeightedDegreeStringKernel, CKernelRidgeRegression, CBaggingMachine, CQDA, CNeuralLayers, CNeuralLogisticLayer, CNeuralRectifiedLinearLayer, CTOPFeatures, CDiceKernelNormalizer, CHierarchicalMultilabelModel, CMultitaskKernelMklNormalizer, CTask, CGaussianProcessClassification, CVwEnvironment, CBinaryLabels, CMultilabelModel, CDomainAdaptationSVMLinear, CMultilabelSOLabels, CCHAIDTree, CKernelTwoSampleTest, CWeightedDegreePositionStringKernel, CMAPInferImpl, CBesselKernel, CTanimotoKernelNormalizer, CCircularBuffer, CMCLDA, CGaussianDistribution, CStreamingHashedDenseFeatures< ST >, CStreamingHashedSparseFeatures< ST >, CAvgDiagKernelNormalizer, CVarianceKernelNormalizer, CMulticlassModel, COnlineLibLinear, CIndexFeatures, CCARTree, CHierarchical, CIndependenceTest, CFKFeatures, CSpectrumMismatchRBFKernel, COperatorFunction< T >, CMultilabelCLRModel, COperatorFunction< float64_t >, CStreamingAsciiFile, CCombinedKernel, CSparseSpatialSampleStringKernel, CVwRegressor, CHashedDocConverter, CFactorGraphLabels, CKLInferenceMethod, CSubsequenceStringKernel, CDotKernel, CGaussianKernel, CCommWordStringKernel, CSet< T >, CDataGenerator, CNeuralInputLayer, CSequenceLabels, CNode, CContingencyTableEvaluation, CPolyFeatures, CDenseMatrixOperator< T >, CLibSVR, CDenseMatrixOperator< float64_t >, CChi2Kernel, CPyramidChi2, CSignal, CSalzbergWordStringKernel, CStructuredLabels, CSquaredHingeLoss, CLPBoost, CNewtonSVM, CKLApproxDiagonalInferenceMethod, CVwLearner, CKLCholeskyInferenceMethod, CKLCovarianceInferenceMethod, CIterativeLinearSolver< T, ST >, CIterativeLinearSolver< float64_t, float64_t >, CIterativeLinearSolver< complex128_t, float64_t >, CIterativeLinearSolver< T, T >, CCommUlongStringKernel, CCompressor, CHomogeneousKernelMap, CSVMLin, CHistogram, CGaussianShiftKernel, CGCArray< T >, CIndexBlockTree, CMultiLaplacianInferenceMethod, CNeuralSoftmaxLayer, CLocallyLinearEmbedding, CMahalanobisDistance, CAttributeFeatures, CRandomFourierDotFeatures, CFirstElementKernelNormalizer, CMap< K, T >, CLogLoss, CLogLossMargin, CSmoothHingeLoss, CSingleLaplacianInferenceMethodWithLBFGS, CScatterSVM, CMap< TParameter *, CSGObject * >, CMap< TParameter *, SGVector< float64_t > >, CGNPPLib, CVwNativeCacheReader, CDistanceKernel, CLatentLabels, CMultilabelLabels, CKLLowerTriangularInferenceMethod, CSoftMaxLikelihood, CMMDKernelSelection, CSpectrumRBFKernel, CSegmentLoss, CKernelDistance, CStreamingFileFromFeatures, CLinearRidgeRegression, CDomainAdaptationSVM, CPolyMatchStringKernel, CSimpleLocalityImprovedStringKernel, CLogDetEstimator, CKernelSelection, CStreamingVwCacheFile, COligoStringKernel, CKLDualInferenceMethod, CEigenSolver, CLPM, CCircularKernel, CConstKernel, CDiagKernel, CSphericalKernel, CLogitDVGLikelihood, CC45ClassifierTree, CMultitaskClusteredLogisticRegression, CEmbeddingConverter, CEuclideanDistance, CWeightedMajorityVote, CMulticlassOVREvaluation, CPolyKernel, CPolyMatchWordStringKernel, CLanczosEigenSolver, CID3ClassifierTree, CNearestCentroid, CMultidimensionalScaling, CStreamingFileFromDenseFeatures< T >, CStreamingFileFromSparseFeatures< T >, CStreamingFileFromStringFeatures< T >, CANOVAKernel, CProductKernel, CSparseKernel< ST >, CGaussianMatchStringKernel, CKernelPCA, CFixedDegreeStringKernel, CStringKernel< ST >, CTensorProductPairKernel, CRandomForest, CTraceSampler, CGaussianNaiveBayes, CMulticlassOneVsRestStrategy, CStringKernel< uint16_t >, CStringKernel< char >, CStringKernel< uint64_t >, CParser, CTStudentKernel, CWaveletKernel, CGaussianProcessRegression, MKLMulticlassGradient, CDiffusionMaps, CMinkowskiMetric, CExponentialKernel, CLaplacianEigenmaps, CAttenuatedEuclideanDistance, CKernelDensity, CCauchyKernel, CLogKernel, CPowerKernel, CRationalQuadraticKernel, CDistantSegmentsKernel, CWaveKernel, CLaplacianInferenceBase, CKernelMachine, CBAHSIC, CLocalityImprovedStringKernel, CMatchWordStringKernel, CRegulatoryModulesStringKernel, CDistanceMachine, CStructuredOutputMachine, CKernelDependenceMaximization, CAUCKernel, CHistogramIntersectionKernel, CSigmoidKernel, CGaussianProcessMachine, CInverseMultiQuadricKernel, CFFDiag, CJADiag, CJADiagOrth, CLibLinearRegression, CMMDKernelSelectionCombOpt, CLocalAlignmentStringKernel, CLabelsFactory, CJediDiag, CQDiag, CUWedge, CTreeMachineNode< T >, CTreeMachineNode< ConditionalProbabilityTreeNodeData >, CTreeMachineNode< RelaxedTreeNodeData >, CTreeMachineNode< id3TreeNodeData >, CTreeMachineNode< VwConditionalProbabilityTreeNodeData >, CTreeMachineNode< CARTreeNodeData >, CTreeMachineNode< C45TreeNodeData >, CTreeMachineNode< CHAIDTreeNodeData >, CTreeMachineNode< NbodyTreeNodeData >, CMulticlassAccuracy, CGaussianARDKernel, CGaussianShortRealKernel, CMultiquadricKernel, CExactInferenceMethod, CPerceptron, CICAConverter, CSplineKernel, CDelimiterTokenizer, CDualVariationalGaussianLikelihood, CLogitVGPiecewiseBoundLikelihood, CLogRationalApproximationIndividual, CDimensionReductionPreprocessor, CGHMM, CHistogramWordStringKernel, CMatrixOperator< T >, CTaskTree, CMatrixOperator< float64_t >, CProbabilityDistribution, CConstMean, CStochasticGBMachine, CLinearOperator< RetType, OperandType >, CCGMShiftedFamilySolver, CIterativeShiftedLinearFamilySolver< T, ST >, CLogRationalApproximationCGM, CTreeMachine< T >, CMMDKernelSelectionCombMaxL2, CMultitaskL12LogisticRegression, CMultitaskROCEvaluation, CLinearOperator< SGVector< complex128_t >, SGVector< complex128_t > >, CLinearOperator< SGVector< T >, SGVector< T > >, CLinearOperator< SGVector< float64_t >, SGVector< float64_t > >, CIterativeShiftedLinearFamilySolver< float64_t, complex128_t >, CTreeMachine< ConditionalProbabilityTreeNodeData >, CTreeMachine< RelaxedTreeNodeData >, CTreeMachine< id3TreeNodeData >, CTreeMachine< VwConditionalProbabilityTreeNodeData >, CTreeMachine< CARTreeNodeData >, CTreeMachine< C45TreeNodeData >, CTreeMachine< CHAIDTreeNodeData >, CTreeMachine< NbodyTreeNodeData >, CCanberraMetric, CCosineDistance, CManhattanMetric, CLineReader, CJensenShannonKernel, CLinearKernel, CNumericalVGLikelihood, CLinearStructuredOutputMachine, CDualLibQPBMSOSVM, CGeodesicMetric, CJensenMetric, CTanimotoDistance, CIdentityKernelNormalizer, CLinearStringKernel, CFITCInferenceMethod, CDecompressString< ST >, CGUIConverter, CNGramTokenizer, CStudentsTVGLikelihood, CMMDKernelSelectionMedian, MKLMulticlassGLPK, CChiSquareDistance, CHammingWordDistance, CLogitVGLikelihood, CProbitVGLikelihood, CRandomSearchModelSelection, CGUILabels, CAveragedPerceptron, CSOBI, CKernelLocallyLinearEmbedding, CSparseDistance< ST >, CCrossValidationResult, CLatentFeatures, CBinaryTreeMachineNode< T >, CMMDKernelSelectionOpt, CSparseDistance< float64_t >, CFFSep, CBrayCurtisDistance, CChebyshewMetric, CFactorGraphFeatures, CRegressionLabels, CJobResultAggregator, CMulticlassOneVsOneStrategy, CNbodyTree, CSparsePreprocessor< ST >, CLeastSquaresRegression, MKLMulticlassOptimizationBase, CVwNativeCacheWriter, CJediSep, CUWedgeSep, CSparseEuclideanDistance, CRealFileFeatures, CLinearARDKernel, CSingleLaplacianInferenceMethod, CDenseMatrixExactLog, CPNorm, CSparseMultilabel, CGUIPluginEstimate, CVwAdaptiveLearner, CStringDistance< ST >, CStructuredAccuracy, CLinearLatentMachine, CMulticlassStrategy, CRescaleFeatures, CStringDistance< uint16_t >, CVwNonAdaptiveLearner, CWeightedDegreeRBFKernel, CIndependentJob, CECOCRandomSparseEncoder, CLogPlusOne, CGradientCriterion, CLatentSVM, CEPInferenceMethod, CGMNPSVM, CNormOne, CMixtureModel, CFactorGraphObservation, CScalarResult< T >, CDirectLinearSolverComplex, CIndividualJobResultAggregator, CMAPInference, CMultitaskTraceLogisticRegression, CLibSVM, CStringFileFeatures< ST >, CLinearMulticlassMachine, CRationalApproximationCGMJob, CBallTree, CKDTree, CStringPreprocessor< ST >, CSumOne, CMultitaskLogisticRegression, CStringPreprocessor< uint16_t >, CStringPreprocessor< uint64_t >, CFastICA, CCanberraWordDistance, CManhattanWordDistance, CCrossValidationOutput, CRationalApproximationIndividualJob, CECOCDiscriminantEncoder, CRandomCARTree, CSortWordString, CResultSet, CTaskGroup, CGUIDistance, CStoreVectorAggregator< T >, CConjugateOrthogonalCGSolver, CPruneVarSubMean, CCCSOSVM, CIntronList, CRealNumber, CStoreVectorAggregator< complex128_t >, CJade, CIndexBlock, CIndexBlockGroup, CGradientModelSelection, CSortUlongString, CSequence, CGUIPreprocessor, CFeatureBlockLogisticRegression, CMeanSquaredError, CMeanSquaredLogError, CLatentSOSVM, CStudentsTLikelihood, CDenseExactLogJob, CMulticlassLibLinear, CMeanAbsoluteError, CDummyFeatures, CListElement, CIsomap, CDenseDistance< ST >, CRealDistance, CIndependentComputationEngine, CVectorResult< T >, CKernelStructuredOutputMachine, CLMNN, CThresholdRejectionStrategy, CMMDKernelSelectionMax, CDenseDistance< float64_t >, CSVMLightOneClass, CLinearLocalTangentSpaceAlignment, CNeighborhoodPreservingEmbedding, CEMBase< T >, CEMMixtureModel, CClusteringAccuracy, CClusteringMutualInformation, CMultilabelAccuracy, CMeanShiftDataGenerator, CVwConditionalProbabilityTree, CEMBase< MixModelData >, CHessianLocallyLinearEmbedding, CCustomMahalanobisDistance, CCombinationRule, CStoreScalarAggregator< T >, CConjugateGradientSolver, CMMDKernelSelectionComb, CFactorGraphModel, CMultitaskLeastSquaresRegression, CLocalTangentSpaceAlignment, CSubsetStack, CGaussianLikelihood, CGridSearchModelSelection, CStochasticSOSVM, CMultitaskLinearMachine, CMajorityVote, CMeanRule, CDirectEigenSolver, CLinearSolver< T, ST >, CLinearSolver< float64_t, float64_t >, CLinearSolver< complex128_t, float64_t >, CLinearSolver< T, T >, CLocalityPreservingProjections, CGradientEvaluation, CSerialComputationEngine, CECOCEncoder, CMulticlassLibSVM, CMKLRegression, CFactorDataSource, CFactorGraph, CTaskRelation, CGaussianBlobsDataGenerator, CIndexBlockRelation, CKernelMeanMatching, CLibSVMOneClass, CROCEvaluation, CKernelMulticlassMachine, CNormalSampler, CBalancedConditionalProbabilityTree, CFactorType, CSOSVMHelper, CDomainAdaptationMulticlassLibLinear, CMKLOneClass, CGPBTSVM, CMPDSVM, CGradientResult, CECOCIHDDecoder, CMulticlassTreeGuidedLogisticRegression, CConditionalProbabilityTree, CRelaxedTree, CFWSOSVM, CMKLClassification, CSubset, CDirectSparseLinearSolver, CECOCRandomDenseEncoder, CMulticlassLogisticRegression, CMulticlassOCAS, CShareBoost, CGNPPSVM, CStratifiedCrossValidationSplitting, CPRCEvaluation, CProbitLikelihood, CSparseInverseCovariance, CCrossValidationSplitting, CDisjointSet, CDenseSubsetFeatures< ST >, CECOCForestEncoder, CGUIMath, CGUITime, CLogitLikelihood, CTDistributedStochasticNeighborEmbedding, CCrossValidationPrintOutput, CJobResult, CECOCDecoder, CFactorAnalysis, CManifoldSculpting, CCrossValidationMKLStorage, SerializableAsciiReader00, CNativeMulticlassMachine, CFunction, CECOCAEDDecoder, CECOCEDDecoder, CECOCStrategy, CData, CZeroMean, CConverter, CLOOCrossValidationSplitting, CBaseMulticlassMachine, CECOCSimpleDecoder, CECOCLLBDecoder, CStructuredData, CECOCHDDecoder, CECOCOVOEncoder, CECOCOVREncoder, CRandomConditionalProbabilityTree, and CRejectionStrategy.

int32_t get_num_labels ( ) const
virtual

get number of labels, depending on whether a subset is set

Returns
number of labels

Implements CLabels.

Definition at line 201 of file DenseLabels.cpp.

float64_t get_value ( int32_t  idx)
virtualinherited

get confidence value for a particular label

Parameters
idxlabel index
Returns
confidence value of label with index idx

Definition at line 59 of file Labels.cpp.

SGVector< float64_t > get_values ( )
virtualinherited

get confidence vector

Returns
confidences

Definition at line 90 of file Labels.cpp.

bool is_generic ( EPrimitiveType *  generic) const
virtualinherited

If the SGSerializable is a class template then TRUE will be returned and GENERIC is set to the type of the generic.

Parameters
genericset to the type of the generic if returning TRUE
Returns
TRUE if a class template.

Definition at line 243 of file SGObject.cpp.

void load ( CFile loader)
virtual

load labels from file

any subset is removed before

Parameters
loaderFile object via which to load data

Definition at line 145 of file DenseLabels.cpp.

DynArray< TParameter * > * load_all_file_parameters ( int32_t  file_version,
int32_t  current_version,
CSerializableFile file,
const char *  prefix = "" 
)
inherited

maps all parameters of this instance to the provided file version and loads all parameter data from the file into an array, which is sorted (basically calls load_file_parameter(...) for all parameters and puts all results into a sorted array)

Parameters
file_versionparameter version of the file
current_versionversion from which mapping begins (you want to use Version::get_version_parameter() for this in most cases)
filefile to load from
prefixprefix for members
Returns
(sorted) array of created TParameter instances with file data

Definition at line 648 of file SGObject.cpp.

DynArray< TParameter * > * load_file_parameters ( const SGParamInfo param_info,
int32_t  file_version,
CSerializableFile file,
const char *  prefix = "" 
)
inherited

loads some specified parameters from a file with a specified version The provided parameter info has a version which is recursively mapped until the file parameter version is reached. Note that there may be possibly multiple parameters in the mapping, therefore, a set of TParameter instances is returned

Parameters
param_infoinformation of parameter
file_versionparameter version of the file, must be <= provided parameter version
filefile to load from
prefixprefix for members
Returns
new array with TParameter instances with the attached data

Definition at line 489 of file SGObject.cpp.

bool load_serializable ( CSerializableFile file,
const char *  prefix = "",
int32_t  param_version = Version::get_version_parameter() 
)
virtualinherited

Load this object from file. If it will fail (returning FALSE) then this object will contain inconsistent data and should not be used!

Parameters
filewhere to load from
prefixprefix for members
param_version(optional) a parameter version different to (this is mainly for testing, better do not use)
Returns
TRUE if done, otherwise FALSE

Definition at line 320 of file SGObject.cpp.

void load_serializable_post ( ) throw (ShogunException)
protectedvirtualinherited

Can (optionally) be overridden to post-initialize some member variables which are not PARAMETER::ADD'ed. Make sure that at first the overridden method BASE_CLASS::LOAD_SERIALIZABLE_POST is called.

Exceptions
ShogunExceptionWill be thrown if an error occurres.

Reimplemented in CKernel, CWeightedDegreePositionStringKernel, CList, CAlphabet, CLinearHMM, CGaussianKernel, CInverseMultiQuadricKernel, CCircularKernel, and CExponentialKernel.

Definition at line 1004 of file SGObject.cpp.

void load_serializable_pre ( ) throw (ShogunException)
protectedvirtualinherited

Can (optionally) be overridden to pre-initialize some member variables which are not PARAMETER::ADD'ed. Make sure that at first the overridden method BASE_CLASS::LOAD_SERIALIZABLE_PRE is called.

Exceptions
ShogunExceptionWill be thrown if an error occurres.

Reimplemented in CDynamicArray< T >, CDynamicArray< float64_t >, CDynamicArray< float32_t >, CDynamicArray< int32_t >, CDynamicArray< char >, CDynamicArray< bool >, and CDynamicObjectArray.

Definition at line 999 of file SGObject.cpp.

void map_parameters ( DynArray< TParameter * > *  param_base,
int32_t &  base_version,
DynArray< const SGParamInfo * > *  target_param_infos 
)
inherited

Takes a set of TParameter instances (base) with a certain version and a set of target parameter infos and recursively maps the base level wise to the current version using CSGObject::migrate(...). The base is replaced. After this call, the base version containing parameters should be of same version/type as the initial target parameter infos. Note for this to work, the migrate methods and all the internal parameter mappings have to match

Parameters
param_baseset of TParameter instances that are mapped to the provided target parameter infos
base_versionversion of the parameter base
target_param_infosset of SGParamInfo instances that specify the target parameter base

Definition at line 686 of file SGObject.cpp.

TParameter * migrate ( DynArray< TParameter * > *  param_base,
const SGParamInfo target 
)
protectedvirtualinherited

creates a new TParameter instance, which contains migrated data from the version that is provided. The provided parameter data base is used for migration, this base is a collection of all parameter data of the previous version. Migration is done FROM the data in param_base TO the provided param info Migration is always one version step. Method has to be implemented in subclasses, if no match is found, base method has to be called.

If there is an element in the param_base which equals the target, a copy of the element is returned. This represents the case when nothing has changed and therefore, the migrate method is not overloaded in a subclass

Parameters
param_baseset of TParameter instances to use for migration
targetparameter info for the resulting TParameter
Returns
a new TParameter instance with migrated data from the base of the type which is specified by the target parameter

Definition at line 893 of file SGObject.cpp.

void one_to_one_migration_prepare ( DynArray< TParameter * > *  param_base,
const SGParamInfo target,
TParameter *&  replacement,
TParameter *&  to_migrate,
char *  old_name = NULL 
)
protectedvirtualinherited

This method prepares everything for a one-to-one parameter migration. One to one here means that only ONE element of the parameter base is needed for the migration (the one with the same name as the target). Data is allocated for the target (in the type as provided in the target SGParamInfo), and a corresponding new TParameter instance is written to replacement. The to_migrate pointer points to the single needed TParameter instance needed for migration. If a name change happened, the old name may be specified by old_name. In addition, the m_delete_data flag of to_migrate is set to true. So if you want to migrate data, the only thing to do after this call is converting the data in the m_parameter fields. If unsure how to use - have a look into an example for this. (base_migration_type_conversion.cpp for example)

Parameters
param_baseset of TParameter instances to use for migration
targetparameter info for the resulting TParameter
replacement(used as output) here the TParameter instance which is returned by migration is created into
to_migratethe only source that is used for migration
old_namewith this parameter, a name change may be specified

Definition at line 833 of file SGObject.cpp.

bool parameter_hash_changed ( )
virtualinherited
Returns
whether parameter combination has changed since last update

Definition at line 209 of file SGObject.cpp.

void print_modsel_params ( )
inherited

prints all parameter registered for model selection and their type

Definition at line 1053 of file SGObject.cpp.

void print_serializable ( const char *  prefix = "")
virtualinherited

prints registered parameters out

Parameters
prefixprefix for members

Definition at line 255 of file SGObject.cpp.

void remove_all_subsets ( )
virtualinherited

removes all subsets Calls subset_changed_post() afterwards

Definition at line 54 of file Labels.cpp.

void remove_subset ( )
virtualinherited

removes that last added subset from subset stack, if existing Calls subset_changed_post() afterwards

Definition at line 49 of file Labels.cpp.

void save ( CFile writer)
virtual

save labels to file

not possible with subset

Parameters
writerFile object via which to save data

Definition at line 152 of file DenseLabels.cpp.

bool save_serializable ( CSerializableFile file,
const char *  prefix = "",
int32_t  param_version = Version::get_version_parameter() 
)
virtualinherited

Save this object to file.

Parameters
filewhere to save the object; will be closed during returning if PREFIX is an empty string.
prefixprefix for members
param_version(optional) a parameter version different to (this is mainly for testing, better do not use)
Returns
TRUE if done, otherwise FALSE

Definition at line 261 of file SGObject.cpp.

void save_serializable_post ( ) throw (ShogunException)
protectedvirtualinherited

Can (optionally) be overridden to post-initialize some member variables which are not PARAMETER::ADD'ed. Make sure that at first the overridden method BASE_CLASS::SAVE_SERIALIZABLE_POST is called.

Exceptions
ShogunExceptionWill be thrown if an error occurres.

Reimplemented in CKernel.

Definition at line 1014 of file SGObject.cpp.

void save_serializable_pre ( ) throw (ShogunException)
protectedvirtualinherited

Can (optionally) be overridden to pre-initialize some member variables which are not PARAMETER::ADD'ed. Make sure that at first the overridden method BASE_CLASS::SAVE_SERIALIZABLE_PRE is called.

Exceptions
ShogunExceptionWill be thrown if an error occurres.

Reimplemented in CKernel, CDynamicArray< T >, CDynamicArray< float64_t >, CDynamicArray< float32_t >, CDynamicArray< int32_t >, CDynamicArray< char >, CDynamicArray< bool >, and CDynamicObjectArray.

Definition at line 1009 of file SGObject.cpp.

void set_generic< complex128_t > ( )
inherited

set generic type to T

Definition at line 38 of file SGObject.cpp.

void set_global_io ( SGIO io)
inherited

set the io object

Parameters
ioio object to use

Definition at line 176 of file SGObject.cpp.

void set_global_parallel ( Parallel parallel)
inherited

set the parallel object

Parameters
parallelparallel object to use

Definition at line 189 of file SGObject.cpp.

void set_global_version ( Version version)
inherited

set the version object

Parameters
versionversion object to use

Definition at line 230 of file SGObject.cpp.

bool set_int_label ( int32_t  idx,
int32_t  label 
)

set INT label

possible with subset

Parameters
idxindex of label to set
labelINT value of label
Returns
if setting was successful

Definition at line 172 of file DenseLabels.cpp.

void set_int_labels ( SGVector< int32_t >  labels)

set INT labels

not possible on subset

Parameters
labelsINT labels

Definition at line 115 of file DenseLabels.cpp.

void set_int_labels ( SGVector< int64_t >  labels)

set INT64 labels

not possible on subset

Parameters
labelsINT labels

Definition at line 127 of file DenseLabels.cpp.

bool set_label ( int32_t  idx,
float64_t  label 
)

set label

possible with subset

Parameters
idxindex of label to set
labelvalue of label
Returns
if setting was successful

Definition at line 160 of file DenseLabels.cpp.

void set_labels ( SGVector< float64_t v)

set labels

not possible with subset

Parameters
vlabels

Definition at line 74 of file DenseLabels.cpp.

void set_to_const ( float64_t  c)

set all labels to a const value

possible with subset

Parameters
cconst to set labels to

Definition at line 63 of file DenseLabels.cpp.

void set_to_one ( )

set all labels to +1

possible with subset

Definition at line 53 of file DenseLabels.cpp.

void set_value ( float64_t  value,
int32_t  idx 
)
virtualinherited

set the confidence value for a particular label

Parameters
valuevalue to set
idxlabel index whose conf. value is to be changed

Definition at line 66 of file Labels.cpp.

void set_values ( SGVector< float64_t values)
virtualinherited

set confidence vector

Parameters
valuesto be set (should have zero length to disable values or length must match the number of labels)

Definition at line 78 of file Labels.cpp.

CSGObject * shallow_copy ( ) const
virtualinherited

A shallow copy. All the SGObject instance variables will be simply assigned and SG_REF-ed.

Reimplemented in CGaussianKernel.

Definition at line 140 of file SGObject.cpp.

void unset_generic ( )
inherited

unset generic type

this has to be called in classes specializing a template class

Definition at line 250 of file SGObject.cpp.

void update_parameter_hash ( )
virtualinherited

Updates the hash of current parameter combination

Definition at line 196 of file SGObject.cpp.

void zero ( )

set all labels to zero

possible with subset

Definition at line 58 of file DenseLabels.cpp.

Member Data Documentation

SGIO* io
inherited

io

Definition at line 461 of file SGObject.h.

SGVector<float64_t> m_current_values
protectedinherited

current active value vector

Definition at line 135 of file Labels.h.

Parameter* m_gradient_parameters
inherited

parameters wrt which we can compute gradients

Definition at line 476 of file SGObject.h.

uint32_t m_hash
inherited

Hash of parameter values

Definition at line 482 of file SGObject.h.

SGVector<float64_t> m_labels
protected

the label vector

Definition at line 210 of file DenseLabels.h.

Parameter* m_model_selection_parameters
inherited

model selection parameters

Definition at line 473 of file SGObject.h.

ParameterMap* m_parameter_map
inherited

map for different parameter versions

Definition at line 479 of file SGObject.h.

Parameter* m_parameters
inherited

parameters

Definition at line 470 of file SGObject.h.

CSubsetStack* m_subset_stack
protectedinherited

subset class to enable subset support for this class

Definition at line 132 of file Labels.h.

Parallel* parallel
inherited

parallel

Definition at line 464 of file SGObject.h.

const int32_t REJECTION_LABEL = -2
static

label designates classify reject

Definition at line 203 of file DenseLabels.h.

Version* version
inherited

version

Definition at line 467 of file SGObject.h.


The documentation for this class was generated from the following files:

SHOGUN Machine Learning Toolbox - Documentation