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SparsePenalty Class Referenceabstract

Detailed Description

The base class for sparse penalty/regularization used in minimization.

This is the interface of regularizers used in minimizers. (eg, FirstOrderMinimizer::update_gradient(SGVector<float64_t> gradient, SGVector<float64_t> var) FirstOrderMinimizer::get_penalty(SGVector<float64_t> var) )

Definition at line 46 of file SparsePenalty.h.

Inheritance diagram for SparsePenalty:
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Public Member Functions

virtual ~SparsePenalty ()
 
virtual float64_t get_sparse_variable (float64_t variable, float64_t penalty_weight)=0
 
virtual void update_variable_for_proximity (SGVector< float64_t > variable, float64_t proximal_weight)=0
 
virtual float64_t get_penalty (float64_t variable)=0
 
virtual float64_t get_penalty_gradient (float64_t variable, float64_t gradient)=0
 
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 ()
 
template<>
void set_generic ()
 
template<>
void set_generic ()
 
template<>
void set_generic ()
 
template<>
void set_generic ()
 
template<>
void set_generic ()
 
template<>
void set_generic ()
 
template<>
void set_generic ()
 
template<>
void set_generic ()
 
template<>
void set_generic ()
 
template<>
void set_generic ()
 
template<>
void set_generic ()
 
template<>
void set_generic ()
 
template<>
void set_generic ()
 
template<>
void set_generic ()
 
template<>
void set_generic ()
 
void unset_generic ()
 
virtual void print_serializable (const char *prefix="")
 
virtual bool save_serializable (CSerializableFile *file, const char *prefix="")
 
virtual bool load_serializable (CSerializableFile *file, const char *prefix="")
 
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)
 
bool has (const std::string &name) const
 
template<typename T >
bool has (const Tag< T > &tag) const
 
template<typename T , typename U = void>
bool has (const std::string &name) const
 
template<typename T >
void set (const Tag< T > &_tag, const T &value)
 
template<typename T , typename U = void>
void set (const std::string &name, const T &value)
 
template<typename T >
get (const Tag< T > &_tag) const
 
template<typename T , typename U = void>
get (const std::string &name) const
 
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
 
uint32_t m_hash
 

Protected Member Functions

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)
 
template<typename T >
void register_param (Tag< T > &_tag, const T &value)
 
template<typename T >
void register_param (const std::string &name, const T &value)
 
bool clone_parameters (CSGObject *other)
 

Constructor & Destructor Documentation

virtual ~SparsePenalty ( )
virtual

Definition at line 49 of file SparsePenalty.h.

Member Function Documentation

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 630 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

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

Definition at line 729 of file SGObject.cpp.

bool clone_parameters ( CSGObject other)
protectedinherited

Definition at line 754 of file SGObject.cpp.

CSGObject * deep_copy ( ) const
virtualinherited

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

Definition at line 231 of file SGObject.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 651 of file SGObject.cpp.

T get ( const Tag< T > &  _tag) const
inherited

Getter for a class parameter, identified by a Tag. Throws an exception if the class does not have such a parameter.

Parameters
_tagname and type information of parameter
Returns
value of the parameter identified by the input tag

Definition at line 376 of file SGObject.h.

T get ( const std::string &  name) const
inherited

Getter for a class parameter, identified by a name. Throws an exception if the class does not have such a parameter.

Parameters
namename of the parameter
Returns
value of the parameter corresponding to the input name and type

Definition at line 399 of file SGObject.h.

SGIO * get_global_io ( )
inherited

get the io object

Returns
io object

Definition at line 268 of file SGObject.cpp.

Parallel * get_global_parallel ( )
inherited

get the parallel object

Returns
parallel object

Definition at line 310 of file SGObject.cpp.

Version * get_global_version ( )
inherited

get the version object

Returns
version object

Definition at line 323 of file SGObject.cpp.

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

Definition at line 531 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 555 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 568 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

Implemented in CMath, CHMM, CStringFeatures< ST >, CStringFeatures< T >, CStringFeatures< uint8_t >, CStringFeatures< char >, CStringFeatures< uint16_t >, CSVMLight, CTrie< Trie >, CTrie< DNATrie >, CTrie< POIMTrie >, CMultitaskKernelTreeNormalizer, CList, CDynamicArray< T >, CDynamicArray< float64_t >, CDynamicArray< float32_t >, CDynamicArray< int32_t >, CDynamicArray< char >, CDynamicArray< bool >, CDynProg, CDenseFeatures< ST >, CDenseFeatures< uint32_t >, CDenseFeatures< float64_t >, CDenseFeatures< T >, CDenseFeatures< uint16_t >, CFile, CSparseFeatures< ST >, CSparseFeatures< float64_t >, CSparseFeatures< T >, CSpecificityMeasure, CPrecisionMeasure, CPlif, CRecallMeasure, CDynamicObjectArray, CSingleFITCLaplaceNewtonOptimizer, CCrossCorrelationMeasure, CLaRank, CCSVFile, CF1Measure, CBinaryFile, CProtobufFile, CWRACCMeasure, CRBM, CBALMeasure, CBitString, CLibSVMFile, CStreamingVwFeatures, CStreamingSparseFeatures< T >, CMemoryMappedFile< T >, CMemoryMappedFile< ST >, CErrorRateMeasure, CNeuralLayer, CMultitaskKernelPlifNormalizer, CMachine, CAccuracyMeasure, CStreamingFile, CStatistics, CRandom, CQuadraticTimeMMD, CMultitaskKernelMaskNormalizer, CAlphabet, CStructuredModel, CLMNNStatistics, CCombinedDotFeatures, CSingleLaplaceNewtonOptimizer, CFeatureSelection< ST >, CFeatureSelection< float64_t >, CMKL, CStreamingDenseFeatures< T >, CStreamingDenseFeatures< float64_t >, CStreamingDenseFeatures< float32_t >, CCache< T >, CCache< uint32_t >, CCache< ST >, CCache< float64_t >, CCache< uint8_t >, CCache< KERNELCACHE_ELEM >, CCache< char >, CCache< uint16_t >, CCache< shogun::SGSparseVectorEntry< T > >, CCache< shogun::SGSparseVectorEntry< float64_t > >, CCache< shogun::SGSparseVectorEntry< ST > >, CSVM, CMMD, CMultitaskKernelMaskPairNormalizer, CNeuralNetwork, CMultitaskKernelNormalizer, CGaussian, CGMM, CHashedWDFeaturesTransposed, CBinaryStream< T >, CLinearHMM, CSimpleFile< T >, CParameterCombination, CDeepBeliefNetwork, CNeuralLinearLayer, CStateModel, CMulticlassSVM, CNeuralConvolutionalLayer, CRandomKitchenSinksDotFeatures, COnlineLinearMachine, CStreamingStringFeatures< T >, CVwParser, CPluginEstimate, CVowpalWabbit, CBinnedDotFeatures, CSVRLight, CPlifMatrix, CHashedWDFeatures, CImplicitWeightedSpecFeatures, CKNN, CLeastAngleRegression, CCombinedFeatures, CSparseMatrixOperator< T >, CSNPFeatures, CWDFeatures, CCrossValidationMulticlassStorage, CHashedDenseFeatures< ST >, CIOBuffer, CUAIFile, CTwoStateModel, CLossFunction, CHMSVMModel, CDeepAutoencoder, CPCA, CHashedSparseFeatures< ST >, CModelSelectionParameters, CRandomFourierGaussPreproc, CMKLMulticlass, CAutoencoder, CHypothesisTest, CExplicitSpecFeatures, CCrossValidation, CMultiKernelQuadraticTimeMMD, CLibLinearMTL, CLinearMachine, CPositionalPWM, CHashedDocDotFeatures, COnlineSVMSGD, CLibLinear, CIntegration, CJacobiEllipticFunctions, CLDA, CTwoDistributionTest, CZeroMeanCenterKernelNormalizer, CSparsePolyFeatures, CHashedMultilabelModel, CSqrtDiagKernelNormalizer, CHuberLoss, CQDA, CCplex, CScatterKernelNormalizer, CKMeansBase, CFisherLDA, CLatentModel, CRationalApproximation, CStochasticProximityEmbedding, CTableFactorType, CSVMSGD, CMulticlassMachine, CDixonQTestRejectionStrategy, CGMNPLib, CVwCacheReader, CLBPPyrDotFeatures, CRidgeKernelNormalizer, CDependenceMaximization, CMulticlassSOLabels, CGraphCut, CSerializableAsciiFile, CKLDualInferenceMethod, CNeuralLayers, CSGDQN, CSNPStringKernel, CMatrixFeatures< ST >, CWeightedCommWordStringKernel, CHingeLoss, CSquaredLoss, CAbsoluteDeviationLoss, CExponentialLoss, CCustomKernel, CTime, CMulticlassLabels, CHash, CFactor, CPlifArray, CSignal, CStreamingHashedDocDotFeatures, CCustomDistance, CStreamingVwFile, CWeightedDegreeStringKernel, CBaggingMachine, CNeuralLogisticLayer, CNeuralRectifiedLinearLayer, CTOPFeatures, CDiceKernelNormalizer, CHierarchicalMultilabelModel, CShiftInvariantKernel, CMultitaskKernelMklNormalizer, CTask, CVwEnvironment, CGaussianKernel, CBinaryLabels, CMultilabelModel, CMultilabelSOLabels, CDomainAdaptationSVMLinear, CGaussianProcessClassification, CDotKernel, CCHAIDTree, CMAPInferImpl, CWeightedDegreePositionStringKernel, CTanimotoKernelNormalizer, CCircularBuffer, CGaussianDistribution, CStreamingHashedDenseFeatures< ST >, CStreamingHashedSparseFeatures< ST >, CBesselKernel, CAvgDiagKernelNormalizer, CVarianceKernelNormalizer, CMCLDA, CMulticlassModel, COnlineLibLinear, CIndexFeatures, CCARTree, CKernelRidgeRegression, CStreamingAsciiFile, CIndependenceTest, CHierarchical, CEuclideanDistance, CFKFeatures, CCombinedKernel, CSparseSpatialSampleStringKernel, CSpectrumMismatchRBFKernel, COperatorFunction< T >, CMultilabelCLRModel, COperatorFunction< float64_t >, CVwRegressor, CHashedDocConverter, CFactorGraphLabels, CCommWordStringKernel, CSubsequenceStringKernel, CSet< T >, CKLInference, CKRRNystrom, CDataGenerator, CSparseInference, CNeuralInputLayer, CTwoSampleTest, CSequenceLabels, CNode, CPolyFeatures, CVwNativeCacheReader, CContingencyTableEvaluation, CChi2Kernel, CPyramidChi2, CLibSVR, CPeriodicKernel, CSalzbergWordStringKernel, CStructuredLabels, CSquaredHingeLoss, CDenseMatrixOperator< T >, CDenseMatrixOperator< float64_t >, CNewtonSVM, CLPBoost, CVwLearner, CIndexBlockTree, CKLDiagonalInferenceMethod, CCommUlongStringKernel, CCompressor, CExactInferenceMethod, CKLCholeskyInferenceMethod, CKLCovarianceInferenceMethod, CIterativeLinearSolver< T, ST >, CIterativeLinearSolver< float64_t, float64_t >, CIterativeLinearSolver< complex128_t, float64_t >, CIterativeLinearSolver< T, T >, CSVMLin, CHistogram, CGaussianShiftKernel, CGCArray< T >, CNeuralSoftmaxLayer, CHomogeneousKernelMap, CMahalanobisDistance, CAttributeFeatures, CRandomFourierDotFeatures, CFirstElementKernelNormalizer, CMap< K, T >, CLogLoss, CLogLossMargin, CSmoothHingeLoss, CMultiLaplaceInferenceMethod, CSingleFITCInference, COneDistributionTest, CStreamingMMD, CMap< shogun::TParameter *, shogun::SGVector< float64_t > >, CMap< shogun::TParameter *, shogun::CSGObject * >, CMap< std::string, T >, CLocallyLinearEmbedding, CDistanceKernel, CLatentLabels, CSoftMaxLikelihood, CScatterSVM, AdamUpdater, FirstOrderStochasticMinimizer, CSpectrumRBFKernel, CMultilabelLabels, CKLLowerTriangularInference, NesterovMomentumCorrection, CSegmentLoss, CKernelDistance, CLogDetEstimator, CLinearRidgeRegression, CGNPPLib, CStreamingFileFromFeatures, CPolyMatchStringKernel, CNeuralLeakyRectifiedLinearLayer, CDomainAdaptationSVM, COligoStringKernel, CSimpleLocalityImprovedStringKernel, CStreamingVwCacheFile, CCircularKernel, CConstKernel, CDiagKernel, CExponentialARDKernel, CSphericalKernel, CEigenSolver, CKNNSolver, CC45ClassifierTree, CLPM, CEmbeddingConverter, CWeightedMajorityVote, CMulticlassOVREvaluation, CPolyKernel, CPolyMatchWordStringKernel, CLogitDVGLikelihood, CSingleFITCLaplaceInferenceMethod, CID3ClassifierTree, CANOVAKernel, CProductKernel, CSparseKernel< ST >, CGaussianMatchStringKernel, CRandomForest, CKernelPCA, CNearestCentroid, CMultidimensionalScaling, CStreamingFileFromDenseFeatures< T >, CStreamingFileFromSparseFeatures< T >, CStreamingFileFromStringFeatures< T >, CFixedDegreeStringKernel, CStringKernel< ST >, CTensorProductPairKernel, CLanczosEigenSolver, CGaussianNaiveBayes, CStringKernel< uint16_t >, CStringKernel< char >, CStringKernel< uint64_t >, CKernelDensity, CParser, CTStudentKernel, CWaveletKernel, CTraceSampler, CMulticlassOneVsRestStrategy, CMinkowskiMetric, CExponentialKernel, CDiffusionMaps, CAttenuatedEuclideanDistance, CCauchyKernel, CLogKernel, CPowerKernel, CRationalQuadraticKernel, CWaveKernel, CEPInferenceMethod, CGaussianProcessRegression, CGEMPLP, CLaplacianEigenmaps, CDistantSegmentsKernel, CLocalityImprovedStringKernel, CMatchWordStringKernel, CRegulatoryModulesStringKernel, CLaplaceInference, CKernelMachine, MKLMulticlassGradient, CAUCKernel, CHistogramIntersectionKernel, CSigmoidKernel, CDistanceMachine, CStructuredOutputMachine, CGaussianARDKernel, CInverseMultiQuadricKernel, CGaussianProcessMachine, CLabelsFactory, CFITCInferenceMethod, CVarDTCInferenceMethod, CFFDiag, CJADiag, CJADiagOrth, CTreeMachineNode< T >, CLibLinearRegression, CTreeMachineNode< ConditionalProbabilityTreeNodeData >, CTreeMachineNode< RelaxedTreeNodeData >, CTreeMachineNode< id3TreeNodeData >, CTreeMachineNode< VwConditionalProbabilityTreeNodeData >, CTreeMachineNode< CARTreeNodeData >, CTreeMachineNode< C45TreeNodeData >, CTreeMachineNode< CHAIDTreeNodeData >, CTreeMachineNode< NbodyTreeNodeData >, CMulticlassAccuracy, CGaussianShortRealKernel, CMultiquadricKernel, CLocalAlignmentStringKernel, CStudentsTLikelihood, CJediDiag, CQDiag, CUWedge, AdaDeltaUpdater, RmsPropUpdater, CSplineKernel, CDelimiterTokenizer, CSingleSparseInference, StandardMomentumCorrection, CDimensionReductionPreprocessor, CPerceptron, CICAConverter, CHistogramWordStringKernel, CDualVariationalGaussianLikelihood, CLogitVGPiecewiseBoundLikelihood, CStudentsTVGLikelihood, FirstOrderMinimizer, CTaskTree, CProbabilityDistribution, CConstMean, CStochasticGBMachine, CMatrixOperator< T >, CLogRationalApproximationIndividual, CTreeMachine< T >, CMultitaskROCEvaluation, CTreeMachine< ConditionalProbabilityTreeNodeData >, CTreeMachine< RelaxedTreeNodeData >, CTreeMachine< id3TreeNodeData >, CTreeMachine< VwConditionalProbabilityTreeNodeData >, CTreeMachine< CARTreeNodeData >, CTreeMachine< C45TreeNodeData >, CTreeMachine< CHAIDTreeNodeData >, CTreeMachine< NbodyTreeNodeData >, CCanberraMetric, CCosineDistance, CManhattanMetric, CJensenShannonKernel, CLinearKernel, CGaussianLikelihood, CIterativeShiftedLinearFamilySolver< T, ST >, CIterativeShiftedLinearFamilySolver< float64_t, complex128_t >, CGeodesicMetric, CJensenMetric, CTanimotoDistance, CLineReader, CIdentityKernelNormalizer, CLinearStringKernel, CNumericalVGLikelihood, CLinearStructuredOutputMachine, CCGMShiftedFamilySolver, CLogRationalApproximationCGM, L1Penalty, SMIDASMinimizer, SVRGMinimizer, CDecompressString< ST >, CKMeans, CNGramTokenizer, CIsomap, CChiSquareDistance, CHammingWordDistance, CRandomSearchModelSelection, MKLMulticlassGLPK, CSparseDistance< ST >, CLatentFeatures, CLogitVGLikelihood, CProbitVGLikelihood, CBinaryTreeMachineNode< T >, CSparseDistance< float64_t >, CAveragedPerceptron, CSOBI, CKernelLocallyLinearEmbedding, CBrayCurtisDistance, CChebyshewMetric, CFactorGraphFeatures, CRegressionLabels, CNbodyTree, SMDMinimizer, CSparsePreprocessor< ST >, CLeastSquaresRegression, MKLMulticlassOptimizationBase, CVwNativeCacheWriter, CFFSep, CSparseEuclideanDistance, CRealFileFeatures, CJobResultAggregator, CGaussianARDSparseKernel, CKLDualInferenceMethodMinimizer, CMulticlassOneVsOneStrategy, AdaptMomentumCorrection, CVwAdaptiveLearner, CJediSep, CUWedgeSep, CStringDistance< ST >, CSingleLaplaceInferenceMethod, CLinearLatentMachine, AdaGradUpdater, CPNorm, CRescaleFeatures, CSparseMultilabel, CStringDistance< uint16_t >, CVwNonAdaptiveLearner, CStructuredAccuracy, CWeightedDegreeRBFKernel, CDenseMatrixExactLog, CECOCRandomSparseEncoder, CMulticlassStrategy, ElasticNetPenalty, InverseScalingLearningRate, L1PenaltyForTG, CGradientCriterion, CIndependentJob, CProbitLikelihood, CGMNPSVM, SGDMinimizer, CLogPlusOne, CMAPInference, CMixtureModel, CFactorGraphObservation, CGradientModelSelection, CNormOne, CLibSVM, CDenseSubSamplesFeatures< ST >, CStringFileFeatures< ST >, CGaussianCompactKernel, CScalarResult< T >, CLogitLikelihood, CBallTree, CKDTree, CStringPreprocessor< ST >, CStringPreprocessor< uint16_t >, CStringPreprocessor< uint64_t >, CFactorAnalysis, CCanberraWordDistance, CManhattanWordDistance, CCrossValidationOutput, CLinearMulticlassMachine, CDirectLinearSolverComplex, CIndividualJobResultAggregator, CECOCDiscriminantEncoder, CRandomCARTree, GradientDescendUpdater, CSumOne, CResultSet, CTaskGroup, CFastICA, CRationalApproximationCGMJob, L2Penalty, PNormMappingFunction, CSortWordString, CCCSOSVM, CIntronList, CRealNumber, CStoreVectorAggregator< T >, CIndexBlock, CIndexBlockGroup, CZeroMean, CRationalApproximationIndividualJob, CLBFGSMinimizer, CPruneVarSubMean, CSequence, CStoreVectorAggregator< complex128_t >, CJade, CMeanSquaredError, CMeanSquaredLogError, CConjugateOrthogonalCGSolver, ConstLearningRate, CSortUlongString, CMeanAbsoluteError, CDummyFeatures, CListElement, CMulticlassLibLinear, CDenseDistance< ST >, CRealDistance, CCrossValidationResult, CStringMap< T >, CDenseExactLogJob, CDenseDistance< float64_t >, CSVMLightOneClass, CEMBase< T >, CEMMixtureModel, CIndependentComputationEngine, CVectorResult< T >, CKernelStructuredOutputMachine, CLMNN, CThresholdRejectionStrategy, CVwConditionalProbabilityTree, CEMBase< MixModelData >, CLinearLocalTangentSpaceAlignment, CNeighborhoodPreservingEmbedding, CCombinationRule, CClusteringAccuracy, CClusteringMutualInformation, CMultilabelAccuracy, CMeanShiftDataGenerator, CBTestMMD, CLinearTimeMMD, CFactorGraphModel, CHessianLocallyLinearEmbedding, CCustomMahalanobisDistance, CSubsetStack, CStoreScalarAggregator< T >, CGridSearchModelSelection, CKDTREEKNNSolver, CStochasticSOSVM, CKMeansMiniBatch, CLocalTangentSpaceAlignment, CMajorityVote, CLinearOperator< T >, CConjugateGradientSolver, CLinearOperator< float64_t >, CLinearOperator< complex128_t >, CMeanRule, CGradientEvaluation, CLinearSolver< T, ST >, CCoverTreeKNNSolver, CMulticlassLibSVM, CMKLRegression, CFactorDataSource, CFactorGraph, CTaskRelation, CLinearSolver< float64_t, float64_t >, CLinearSolver< complex128_t, float64_t >, CLinearSolver< T, T >, CLocalityPreservingProjections, CSerialComputationEngine, CIndexBlockRelation, CDirectEigenSolver, CECOCEncoder, CGradientResult, CROCEvaluation, CGaussianBlobsDataGenerator, CBruteKNNSolver, CBalancedConditionalProbabilityTree, CFactorType, CSOSVMHelper, CMKLOneClass, CLibSVMOneClass, CMPDSVM, CKernelMulticlassMachine, CNormalSampler, CECOCIHDDecoder, CConditionalProbabilityTree, CRelaxedTree, CFWSOSVM, CDomainAdaptationMulticlassLibLinear, CMKLClassification, CSubset, CECOCRandomDenseEncoder, CShareBoost, CGNPPSVM, CFactorGraphDataGenerator, CPRCEvaluation, CStratifiedCrossValidationSplitting, CDirectSparseLinearSolver, CDisjointSet, CCrossValidationSplitting, CDenseSubsetFeatures< ST >, CECOCForestEncoder, CCrossValidationPrintOutput, CTDistributedStochasticNeighborEmbedding, CCrossValidationMKLStorage, SerializableAsciiReader00, CJobResult, CFunction, CECOCAEDDecoder, CECOCDecoder, CECOCEDDecoder, CManifoldSculpting, CData, CNativeMulticlassMachine, CECOCStrategy, CConverter, CBaseMulticlassMachine, CECOCSimpleDecoder, CLOOCrossValidationSplitting, CECOCLLBDecoder, CStructuredData, CECOCHDDecoder, CRandomConditionalProbabilityTree, CECOCOVOEncoder, CECOCOVREncoder, and CRejectionStrategy.

virtual float64_t get_penalty ( float64_t  variable)
pure virtualinherited

Given the value of a target variable, this method returns the penalty of the variable

For L2 penalty, \(L2(w)\)

\[ L2(w)=\frac{w^t w}{2} \]

Parameters
variablevalue of the variable
Returns
penalty of the variable

Implemented in ElasticNetPenalty, L2Penalty, and L1Penalty.

virtual float64_t get_penalty_gradient ( float64_t  variable,
float64_t  gradient 
)
pure virtualinherited

Returns the gradient of the penalty wrt a target variable Note that the penalized gradient=unpenalized gradient+penalty_gradient

For L2 penalty

\[ \frac{\partial L2(w) }{\partial w}=w \]

Parameters
variablevalue of a target variable
gradientunregularized/unpenalized gradient of the variable
Returns
the gradient of the penalty wrt the variable

Implemented in ElasticNetPenalty, L1Penalty, and L2Penalty.

virtual float64_t get_sparse_variable ( float64_t  variable,
float64_t  penalty_weight 
)
pure virtual

Get the sparse variable

Parameters
variablethe raw variable
penalty_weightweight of the penalty
Returns
sparse value of the variable

Implemented in ElasticNetPenalty, and L1Penalty.

bool has ( const std::string &  name) const
inherited

Checks if object has a class parameter identified by a name.

Parameters
namename of the parameter
Returns
true if the parameter exists with the input name

Definition at line 299 of file SGObject.h.

bool has ( const Tag< T > &  tag) const
inherited

Checks if object has a class parameter identified by a Tag.

Parameters
tagtag of the parameter containing name and type information
Returns
true if the parameter exists with the input tag

Definition at line 310 of file SGObject.h.

bool has ( const std::string &  name) const
inherited

Checks if a type exists for a class parameter identified by a name.

Parameters
namename of the parameter
Returns
true if the parameter exists with the input name and type

Definition at line 321 of file SGObject.h.

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 329 of file SGObject.cpp.

bool load_serializable ( CSerializableFile file,
const char *  prefix = "" 
)
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
Returns
TRUE if done, otherwise FALSE

Definition at line 402 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 occurs.

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

Definition at line 459 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 occurs.

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

Definition at line 454 of file SGObject.cpp.

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

Definition at line 295 of file SGObject.cpp.

void print_modsel_params ( )
inherited

prints all parameter registered for model selection and their type

Definition at line 507 of file SGObject.cpp.

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

prints registered parameters out

Parameters
prefixprefix for members

Definition at line 341 of file SGObject.cpp.

void register_param ( Tag< T > &  _tag,
const T &  value 
)
protectedinherited

Registers a class parameter which is identified by a tag. This enables the parameter to be modified by set() and retrieved by get(). Parameters can be registered in the constructor of the class.

Parameters
_tagname and type information of parameter
valuevalue of the parameter

Definition at line 450 of file SGObject.h.

void register_param ( const std::string &  name,
const T &  value 
)
protectedinherited

Registers a class parameter which is identified by a name. This enables the parameter to be modified by set() and retrieved by get(). Parameters can be registered in the constructor of the class.

Parameters
namename of the parameter
valuevalue of the parameter along with type information

Definition at line 463 of file SGObject.h.

bool save_serializable ( CSerializableFile file,
const char *  prefix = "" 
)
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
Returns
TRUE if done, otherwise FALSE

Definition at line 347 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 occurs.

Reimplemented in CKernel.

Definition at line 469 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 occurs.

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

Definition at line 464 of file SGObject.cpp.

void set ( const Tag< T > &  _tag,
const T &  value 
)
inherited

Setter for a class parameter, identified by a Tag. Throws an exception if the class does not have such a parameter.

Parameters
_tagname and type information of parameter
valuevalue of the parameter

Definition at line 337 of file SGObject.h.

void set ( const std::string &  name,
const T &  value 
)
inherited

Setter for a class parameter, identified by a name. Throws an exception if the class does not have such a parameter.

Parameters
namename of the parameter
valuevalue of the parameter along with type information

Definition at line 363 of file SGObject.h.

void set_generic ( )
inherited

Definition at line 74 of file SGObject.cpp.

void set_generic ( )
inherited

Definition at line 79 of file SGObject.cpp.

void set_generic ( )
inherited

Definition at line 84 of file SGObject.cpp.

void set_generic ( )
inherited

Definition at line 89 of file SGObject.cpp.

void set_generic ( )
inherited

Definition at line 94 of file SGObject.cpp.

void set_generic ( )
inherited

Definition at line 99 of file SGObject.cpp.

void set_generic ( )
inherited

Definition at line 104 of file SGObject.cpp.

void set_generic ( )
inherited

Definition at line 109 of file SGObject.cpp.

void set_generic ( )
inherited

Definition at line 114 of file SGObject.cpp.

void set_generic ( )
inherited

Definition at line 119 of file SGObject.cpp.

void set_generic ( )
inherited

Definition at line 124 of file SGObject.cpp.

void set_generic ( )
inherited

Definition at line 129 of file SGObject.cpp.

void set_generic ( )
inherited

Definition at line 134 of file SGObject.cpp.

void set_generic ( )
inherited

Definition at line 139 of file SGObject.cpp.

void set_generic ( )
inherited

Definition at line 144 of file SGObject.cpp.

void set_generic ( )
inherited

set generic type to T

void set_global_io ( SGIO io)
inherited

set the io object

Parameters
ioio object to use

Definition at line 261 of file SGObject.cpp.

void set_global_parallel ( Parallel parallel)
inherited

set the parallel object

Parameters
parallelparallel object to use

Definition at line 274 of file SGObject.cpp.

void set_global_version ( Version version)
inherited

set the version object

Parameters
versionversion object to use

Definition at line 316 of file SGObject.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 225 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 336 of file SGObject.cpp.

void update_parameter_hash ( )
virtualinherited

Updates the hash of current parameter combination

Definition at line 281 of file SGObject.cpp.

virtual void update_variable_for_proximity ( SGVector< float64_t variable,
float64_t  proximal_weight 
)
pure virtualinherited

Do proximal projection/operation in place

Parameters
variablethe raw variable
proximal_weightweight of the penalty

Implemented in ElasticNetPenalty, L1Penalty, and L1PenaltyForTG.

Member Data Documentation

SGIO* io
inherited

io

Definition at line 558 of file SGObject.h.

Parameter* m_gradient_parameters
inherited

parameters wrt which we can compute gradients

Definition at line 573 of file SGObject.h.

uint32_t m_hash
inherited

Hash of parameter values

Definition at line 576 of file SGObject.h.

Parameter* m_model_selection_parameters
inherited

model selection parameters

Definition at line 570 of file SGObject.h.

Parameter* m_parameters
inherited

parameters

Definition at line 567 of file SGObject.h.

Parallel* parallel
inherited

parallel

Definition at line 561 of file SGObject.h.

Version* version
inherited

version

Definition at line 564 of file SGObject.h.


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

SHOGUN Machine Learning Toolbox - Documentation