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CDistance Class Referenceabstract

Detailed Description

Class Distance, a base class for all the distances used in the Shogun toolbox.

The distance (or metric) is a function \( d: X \times X \to R \) satisfying (for all \( x,y,z \in X\)) conditions below:

Currently distance inherited from the CDistance class should be symmetric.

The simplest example of a distance function is the Euclidean distance:

See also
CEuclideanDistance

In the means of Shogun toolbox the distance function is defined on the 'space' of CFeatures.

Precomputations can be done for left hand side and right hand side features. This has to be implemented in overloaded methods for precompute_lhs() and precompute_rhs() in derived classes. WARNING : Make sure to reset precomputations for features using reset_precompute() when features or feature matrix are changed.

Definition at line 87 of file Distance.h.

Inheritance diagram for CDistance:
[legend]

Public Member Functions

 CDistance ()
 
 CDistance (CFeatures *lhs, CFeatures *rhs)
 
virtual ~CDistance ()
 
virtual float64_t distance (int32_t idx_a, int32_t idx_b)
 
virtual float64_t distance_upper_bounded (int32_t idx_a, int32_t idx_b, float64_t upper_bound)
 
virtual void precompute_rhs ()
 
virtual void precompute_lhs ()
 
virtual void reset_precompute ()
 
SGMatrix< float64_tget_distance_matrix ()
 
template<class T >
SGMatrix< T > get_distance_matrix ()
 
int32_t compute_row_start (int64_t offs, int32_t n, bool symmetric)
 
virtual bool init (CFeatures *lhs, CFeatures *rhs)
 
virtual void cleanup ()=0
 
void load (CFile *loader)
 
void save (CFile *writer)
 
CFeaturesget_lhs ()
 
CFeaturesget_rhs ()
 
CFeaturesreplace_rhs (CFeatures *rhs)
 
CFeaturesreplace_lhs (CFeatures *lhs)
 
virtual void remove_lhs_and_rhs ()
 
virtual void remove_lhs ()
 takes all necessary steps if the lhs is removed from distance matrix More...
 
virtual void remove_rhs ()
 takes all necessary steps if the rhs is removed from distance matrix More...
 
virtual EDistanceType get_distance_type ()=0
 
virtual EFeatureType get_feature_type ()=0
 
virtual EFeatureClass get_feature_class ()=0
 
bool get_precompute_matrix ()
 
virtual void set_precompute_matrix (bool flag)
 
virtual int32_t get_num_vec_lhs ()
 
virtual int32_t get_num_vec_rhs ()
 
virtual bool has_features ()
 
bool lhs_equals_rhs ()
 
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)
 
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 ()
 

Static Public Member Functions

template<class T >
static void * get_distance_matrix_helper (void *p)
 

Public Attributes

SGIOio
 
Parallelparallel
 
Versionversion
 
Parameterm_parameters
 
Parameterm_model_selection_parameters
 
Parameterm_gradient_parameters
 
uint32_t m_hash
 

Protected Member Functions

virtual float64_t compute (int32_t idx_a, int32_t idx_b)=0
 
void do_precompute_matrix ()
 matrix precomputation More...
 
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)
 

Static Protected Member Functions

static void * run_distance_thread (void *p)
 run distance thread More...
 

Protected Attributes

float32_tprecomputed_matrix
 
bool precompute_matrix
 
CFeatureslhs
 feature vectors to occur on the left hand side More...
 
CFeaturesrhs
 feature vectors to occur on the right hand side More...
 
int32_t num_lhs
 
int32_t num_rhs
 

Constructor & Destructor Documentation

CDistance ( )

default constructor

Definition at line 58 of file Distance.cpp.

CDistance ( CFeatures lhs,
CFeatures rhs 
)

init distance

Parameters
lhsfeatures of left-hand side
rhsfeatures of right-hand side
Returns
if init was successful

Definition at line 64 of file Distance.cpp.

~CDistance ( )
virtual

Definition at line 70 of file Distance.cpp.

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 597 of file SGObject.cpp.

virtual void cleanup ( )
pure virtual
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 714 of file SGObject.cpp.

virtual float64_t compute ( int32_t  idx_a,
int32_t  idx_b 
)
protectedpure virtual
int32_t compute_row_start ( int64_t  offs,
int32_t  n,
bool  symmetric 
)

compute row start offset for parallel kernel matrix computation

Parameters
offsoffset
nnumber of columns
symmetricwhether matrix is symmetric

Definition at line 173 of file Distance.h.

CSGObject * deep_copy ( ) const
virtualinherited

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

Definition at line 198 of file SGObject.cpp.

float64_t distance ( int32_t  idx_a,
int32_t  idx_b 
)
virtual

get distance function for lhs feature vector a and rhs feature vector b

Parameters
idx_afeature vector a at idx_a
idx_bfeature vector b at idx_b
Returns
distance value

Definition at line 189 of file Distance.cpp.

virtual float64_t distance_upper_bounded ( int32_t  idx_a,
int32_t  idx_b,
float64_t  upper_bound 
)
virtual

get distance function for lhs feature vector a and rhs feature vector b. The computation of the distance stops if the intermediate result is larger than upper_bound. This is useful to use with John Langford's Cover Tree and it is ONLY implemented for Euclidean distance

Parameters
idx_afeature vector a at idx_a
idx_bfeature vector b at idx_b
upper_boundvalue above which the computation halts
Returns
distance value or upper_bound

Reimplemented in CEuclideanDistance.

Definition at line 124 of file Distance.h.

void do_precompute_matrix ( )
protected

matrix precomputation

Definition at line 227 of file Distance.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 618 of file SGObject.cpp.

template SGMatrix< float32_t > get_distance_matrix< float32_t > ( )

get distance matrix

Returns
computed distance matrix (needs to be cleaned up)

Definition at line 156 of file Distance.h.

SGMatrix< T > get_distance_matrix ( )

get distance matrix (templated)

Returns
the distance matrix

Definition at line 317 of file Distance.cpp.

template void * get_distance_matrix_helper< float32_t > ( void *  p)
static

helper for computing the kernel matrix in a parallel way

Parameters
pthread parameters

Definition at line 266 of file Distance.cpp.

virtual EDistanceType get_distance_type ( )
pure virtual
virtual EFeatureClass get_feature_class ( )
pure virtual

get feature class the distance can deal with

abstract base method

Returns
feature class

Implemented in CCustomDistance, CKernelDistance, CSparseDistance< ST >, CSparseDistance< float64_t >, CStringDistance< ST >, CStringDistance< uint16_t >, CDenseDistance< ST >, and CDenseDistance< float64_t >.

virtual EFeatureType get_feature_type ( )
pure virtual
SGIO * get_global_io ( )
inherited

get the io object

Returns
io object

Definition at line 235 of file SGObject.cpp.

Parallel * get_global_parallel ( )
inherited

get the parallel object

Returns
parallel object

Definition at line 277 of file SGObject.cpp.

Version * get_global_version ( )
inherited

get the version object

Returns
version object

Definition at line 290 of file SGObject.cpp.

CFeatures* get_lhs ( )

get left-hand side features used in distance matrix

Returns
left-hand side features

Definition at line 224 of file Distance.h.

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

Definition at line 498 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 522 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 535 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 >, CDynamicArray< T >, CDynamicArray< float64_t >, CDynamicArray< float32_t >, CDynamicArray< int32_t >, CDynamicArray< char >, CDynamicArray< bool >, CMultitaskKernelTreeNormalizer, CList, 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, CCrossCorrelationMeasure, CLaRank, CCSVFile, CF1Measure, CBinaryFile, CProtobufFile, CWRACCMeasure, CRBM, CTaxonomy, CBALMeasure, CBitString, CStreamingVwFeatures, CLibSVMFile, CStreamingSparseFeatures< T >, CErrorRateMeasure, CNeuralLayer, CMultitaskKernelPlifNormalizer, CMachine, CAccuracyMeasure, CStreamingFile, CStatistics, CQuadraticTimeMMD, CRandom, CStreamingMMD, CMemoryMappedFile< T >, CMultitaskKernelMaskNormalizer, CMemoryMappedFile< ST >, CAlphabet, CMKL, CStructuredModel, CStreamingDenseFeatures< T >, CLMNNStatistics, CStreamingDenseFeatures< float64_t >, CStreamingDenseFeatures< float32_t >, CCombinedDotFeatures, CFeatureSelection< ST >, CFeatureSelection< float64_t >, CGUIStructure, 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 > >, CMultitaskKernelMaskPairNormalizer, CSVM, CNeuralNetwork, CMultitaskKernelNormalizer, CGUIClassifier, CGaussian, CGUIFeatures, CGMM, CHashedWDFeaturesTransposed, CBinaryStream< T >, CLinearHMM, CSimpleFile< T >, CStreamingStringFeatures< T >, CParameterCombination, CDeepBeliefNetwork, CNeuralLinearLayer, CStateModel, CMulticlassSVM, CNeuralConvolutionalLayer, CRandomKitchenSinksDotFeatures, COnlineLinearMachine, CVwParser, CPluginEstimate, CVowpalWabbit, CBinnedDotFeatures, CSVRLight, CPlifMatrix, CHashedWDFeatures, CImplicitWeightedSpecFeatures, CCombinedFeatures, CSparseMatrixOperator< T >, CSNPFeatures, CWDFeatures, CKMeans, CCrossValidationMulticlassStorage, CHashedDenseFeatures< ST >, CIOBuffer, CUAIFile, CTwoStateModel, CLossFunction, CKNN, CHMSVMModel, CDeepAutoencoder, CPCA, CLeastAngleRegression, CGUIKernel, CHashedSparseFeatures< ST >, CRandomFourierGaussPreproc, CMKLMulticlass, CAutoencoder, CHypothesisTest, CExplicitSpecFeatures, CLibLinearMTL, CLinearMachine, CModelSelectionParameters, CPositionalPWM, CCrossValidation, CNOCCO, CHashedDocDotFeatures, CGUIHMM, COnlineSVMSGD, CLibLinear, CIntegration, CJacobiEllipticFunctions, CLDA, CZeroMeanCenterKernelNormalizer, CSparsePolyFeatures, CHashedMultilabelModel, CSqrtDiagKernelNormalizer, CHuberLoss, CCplex, CScatterKernelNormalizer, CFisherLDA, CHSIC, CLatentModel, CRationalApproximation, CStochasticProximityEmbedding, CTableFactorType, CSVMSGD, CMulticlassMachine, CDixonQTestRejectionStrategy, CGMNPLib, CVwCacheReader, CLBPPyrDotFeatures, CRidgeKernelNormalizer, CDependenceMaximization, CMulticlassSOLabels, CGraphCut, CSerializableAsciiFile, CSGDQN, CSNPStringKernel, CTime, CMatrixFeatures< ST >, CWeightedCommWordStringKernel, CHingeLoss, CKLDualInferenceMethod, CNeuralLayers, CTwoSampleTest, CSquaredLoss, CAbsoluteDeviationLoss, CExponentialLoss, CCustomKernel, CMulticlassLabels, CHash, CFactor, CPlifArray, CLinearTimeMMD, CStreamingHashedDocDotFeatures, CStreamingVwFile, CKernelIndependenceTest, CCustomDistance, CWeightedDegreeStringKernel, CBaggingMachine, CQDA, CNeuralLogisticLayer, CNeuralRectifiedLinearLayer, CTOPFeatures, CDiceKernelNormalizer, CHierarchicalMultilabelModel, CMultitaskKernelMklNormalizer, CTask, CVwEnvironment, CBinaryLabels, CMultilabelModel, CMultilabelSOLabels, CDomainAdaptationSVMLinear, CGaussianProcessClassification, CDotKernel, CCHAIDTree, CKernelTwoSampleTest, CMAPInferImpl, CWeightedDegreePositionStringKernel, CTanimotoKernelNormalizer, CCircularBuffer, CGaussianDistribution, CStreamingHashedDenseFeatures< ST >, CStreamingHashedSparseFeatures< ST >, CBesselKernel, CAvgDiagKernelNormalizer, CVarianceKernelNormalizer, CMCLDA, CMulticlassModel, COnlineLibLinear, CIndexFeatures, CCARTree, CKernelRidgeRegression, CStreamingAsciiFile, CIndependenceTest, CHierarchical, CFKFeatures, CCombinedKernel, CSparseSpatialSampleStringKernel, CSpectrumMismatchRBFKernel, COperatorFunction< T >, CMultilabelCLRModel, COperatorFunction< float64_t >, CVwRegressor, CHashedDocConverter, CFactorGraphLabels, CCommWordStringKernel, CSubsequenceStringKernel, CSet< T >, CKLInference, CDataGenerator, CSparseInference, CNeuralInputLayer, CSequenceLabels, CPolyFeatures, CNode, CContingencyTableEvaluation, CChi2Kernel, CPyramidChi2, CSignal, 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, CGaussianKernel, CGaussianShiftKernel, CGCArray< T >, CNeuralSoftmaxLayer, CHomogeneousKernelMap, CEuclideanDistance, CMahalanobisDistance, CAttributeFeatures, CRandomFourierDotFeatures, CFirstElementKernelNormalizer, CMap< K, T >, CWrappedObjectArray, CLogLoss, CLogLossMargin, CSmoothHingeLoss, CMultiLaplaceInferenceMethod, CSingleFITCInference, CMap< shogun::TParameter *, shogun::SGVector< float64_t > >, CMap< shogun::TParameter *, shogun::CSGObject * >, CMap< std::string, int32_t >, CMap< std::string, shogun::SGVector< float64_t > >, CMap< std::string, T >, CMap< std::string, float64_t >, CVwNativeCacheReader, CLocallyLinearEmbedding, CDistanceKernel, CLatentLabels, CSoftMaxLikelihood, CScatterSVM, CSpectrumRBFKernel, CMultilabelLabels, CKLLowerTriangularInference, CMMDKernelSelection, CSegmentLoss, CKernelDistance, CLinearRidgeRegression, CGNPPLib, CStreamingFileFromFeatures, CPolyMatchStringKernel, CWrappedBasic< T >, CNeuralLeakyRectifiedLinearLayer, CDomainAdaptationSVM, COligoStringKernel, CSimpleLocalityImprovedStringKernel, CLogDetEstimator, CKernelSelection, CStreamingVwCacheFile, CCircularKernel, CConstKernel, CDiagKernel, CExponentialARDKernel, CSphericalKernel, CEigenSolver, 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, CBAHSIC, MKLMulticlassGradient, CAUCKernel, CHistogramIntersectionKernel, CSigmoidKernel, CDistanceMachine, CStructuredOutputMachine, CKernelDependenceMaximization, 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, CSplineKernel, CDelimiterTokenizer, CWrappedSGMatrix< T >, CWrappedSGVector< T >, CDimensionReductionPreprocessor, CPerceptron, CICAConverter, CHistogramWordStringKernel, CDualVariationalGaussianLikelihood, CLogitVGPiecewiseBoundLikelihood, CSingleSparseInference, CStudentsTVGLikelihood, 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, CDecompressString< ST >, CGUIConverter, CNGramTokenizer, CMMDKernelSelectionMedian, CIsomap, CChiSquareDistance, CHammingWordDistance, CRandomSearchModelSelection, CGUILabels, MKLMulticlassGLPK, CSparseDistance< ST >, CLatentFeatures, CLogitVGLikelihood, CProbitVGLikelihood, CBinaryTreeMachineNode< T >, CMMDKernelSelectionOpt, CSparseDistance< float64_t >, CAveragedPerceptron, CSOBI, CKernelLocallyLinearEmbedding, CBrayCurtisDistance, CChebyshewMetric, CFactorGraphFeatures, CRegressionLabels, CNbodyTree, CMinimizerContext, CSparsePreprocessor< ST >, CLeastSquaresRegression, MKLMulticlassOptimizationBase, CVwNativeCacheWriter, CFFSep, CSparseEuclideanDistance, CRealFileFeatures, CJobResultAggregator, CGaussianARDSparseKernel, CMulticlassOneVsOneStrategy, CGUIPluginEstimate, CVwAdaptiveLearner, CJediSep, CUWedgeSep, CStringDistance< ST >, CSingleLaplaceInferenceMethod, CLinearLatentMachine, CPNorm, CRescaleFeatures, CSparseMultilabel, CStringDistance< uint16_t >, CVwNonAdaptiveLearner, CStructuredAccuracy, CWeightedDegreeRBFKernel, CDenseMatrixExactLog, CECOCRandomSparseEncoder, CMulticlassStrategy, CGradientCriterion, CIndependentJob, CProbitLikelihood, CGMNPSVM, CLogPlusOne, CMAPInference, CMixtureModel, CFactorGraphObservation, 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, CSumOne, CResultSet, CTaskGroup, CGUIDistance, CFastICA, CRationalApproximationCGMJob, CSortWordString, CCCSOSVM, CIntronList, CRealNumber, CStoreVectorAggregator< T >, CIndexBlock, CIndexBlockGroup, CZeroMean, CRationalApproximationIndividualJob, CPruneVarSubMean, CSequence, CGUIPreprocessor, CStoreVectorAggregator< complex128_t >, CJade, CMeanSquaredError, CMeanSquaredLogError, CConjugateOrthogonalCGSolver, CSortUlongString, CMeanAbsoluteError, CDummyFeatures, CListElement, CMulticlassLibLinear, CDenseDistance< ST >, CRealDistance, CCrossValidationResult, CStringMap< T >, CDenseExactLogJob, CMMDKernelSelectionMax, CDenseDistance< float64_t >, CStringMap< float64_t >, CStringMap< shogun::SGVector< float64_t > >, CStringMap< int32_t >, CSVMLightOneClass, CEMBase< T >, CEMMixtureModel, CIndependentComputationEngine, CVectorResult< T >, CKernelStructuredOutputMachine, CLMNN, CThresholdRejectionStrategy, CVwConditionalProbabilityTree, CEMBase< MixModelData >, CLinearLocalTangentSpaceAlignment, CNeighborhoodPreservingEmbedding, CCombinationRule, CClusteringAccuracy, CClusteringMutualInformation, CMultilabelAccuracy, CMeanShiftDataGenerator, CFactorGraphModel, CHessianLocallyLinearEmbedding, CCustomMahalanobisDistance, CSubsetStack, CStoreScalarAggregator< T >, CGridSearchModelSelection, CStochasticSOSVM, CLocalTangentSpaceAlignment, CMajorityVote, CLinearOperator< T >, CConjugateGradientSolver, CLinearOperator< float64_t >, CLinearOperator< complex128_t >, CMeanRule, CGradientEvaluation, CLinearSolver< T, ST >, CMulticlassLibSVM, CMKLRegression, CFactorDataSource, CFactorGraph, CTaskRelation, CLinearSolver< float64_t, float64_t >, CLinearSolver< complex128_t, float64_t >, CLinearSolver< T, T >, CLocalityPreservingProjections, CSerialComputationEngine, CIndexBlockRelation, CDirectEigenSolver, CECOCEncoder, CROCEvaluation, CGaussianBlobsDataGenerator, CBalancedConditionalProbabilityTree, CFactorType, CSOSVMHelper, CMKLOneClass, CLibSVMOneClass, CMPDSVM, CGradientResult, CKernelMulticlassMachine, CNormalSampler, CECOCIHDDecoder, CConditionalProbabilityTree, CRelaxedTree, CFWSOSVM, CDomainAdaptationMulticlassLibLinear, CMKLClassification, CSubset, CECOCRandomDenseEncoder, CShareBoost, CGNPPSVM, CFactorGraphDataGenerator, CPRCEvaluation, CStratifiedCrossValidationSplitting, CDirectSparseLinearSolver, CDisjointSet, CCrossValidationSplitting, CDenseSubsetFeatures< ST >, CECOCForestEncoder, CGUIMath, CGUITime, 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 int32_t get_num_vec_lhs ( )
virtual

get number of vectors of lhs features

Returns
number of vectors of left-hand side

Reimplemented in CCustomDistance.

Definition at line 312 of file Distance.h.

virtual int32_t get_num_vec_rhs ( )
virtual

get number of vectors of rhs features

Returns
number of vectors of right-hand side

Reimplemented in CCustomDistance.

Definition at line 321 of file Distance.h.

bool get_precompute_matrix ( )

FIXME: precompute matrix should be dropped, handling should be via customdistance

Returns
if precompute_matrix

Definition at line 290 of file Distance.h.

CFeatures* get_rhs ( )

get right-hand side features used in distance matrix

Returns
right-hand side features

Definition at line 230 of file Distance.h.

virtual bool has_features ( )
virtual

test whether features have been assigned to lhs and rhs

Returns
true if features are assigned

Reimplemented in CCustomDistance.

Definition at line 330 of file Distance.h.

bool init ( CFeatures lhs,
CFeatures rhs 
)
virtual
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 296 of file SGObject.cpp.

bool lhs_equals_rhs ( )

test whether features on lhs and rhs are the same

Returns
true if features are the same

Definition at line 339 of file Distance.h.

void load ( CFile loader)

load the kernel matrix

Parameters
loaderFile object via which to load data

Definition at line 107 of file Distance.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 369 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 426 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 421 of file SGObject.cpp.

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

Definition at line 262 of file SGObject.cpp.

virtual void precompute_lhs ( )
virtual

Precomputation related to features of left hand side WARNING : Make sure to reset computations using reset_precompute() when features or feature matrix are changed. This method is empty, should be overloaded in derived class.

Reimplemented in CEuclideanDistance.

Definition at line 143 of file Distance.h.

virtual void precompute_rhs ( )
virtual

Precomputation related to features of right hand side WARNING : Make sure to reset computations using reset_precompute() when features or feature matrix are changed. This method is empty, should be overloaded in derived class.

Reimplemented in CEuclideanDistance.

Definition at line 135 of file Distance.h.

void print_modsel_params ( )
inherited

prints all parameter registered for model selection and their type

Definition at line 474 of file SGObject.cpp.

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

prints registered parameters out

Parameters
prefixprefix for members

Definition at line 308 of file SGObject.cpp.

void remove_lhs ( )
virtual

takes all necessary steps if the lhs is removed from distance matrix

Definition at line 130 of file Distance.cpp.

void remove_lhs_and_rhs ( )
virtual

remove lhs and rhs from distance

Definition at line 119 of file Distance.cpp.

void remove_rhs ( )
virtual

takes all necessary steps if the rhs is removed from distance matrix

takes all necessary steps if the rhs is removed from distance

Definition at line 138 of file Distance.cpp.

CFeatures * replace_lhs ( CFeatures lhs)

replace left-hand side features used in distance matrix

make sure to check that your distance can deal with the supplied features (!)

Parameters
lhsfeatures of right-hand side
Returns
replaced left-hand side features

Definition at line 167 of file Distance.cpp.

CFeatures * replace_rhs ( CFeatures rhs)

replace right-hand side features used in distance matrix

make sure to check that your distance can deal with the supplied features (!)

Parameters
rhsfeatures of right-hand side
Returns
replaced right-hand side features

Definition at line 145 of file Distance.cpp.

virtual void reset_precompute ( )
virtual

Reset precomputations for features of both sides Should be used to reset whenever features or feature matrix are changed. This method is empty, should be overloaded in derived class.

Reimplemented in CEuclideanDistance.

Definition at line 150 of file Distance.h.

static void* run_distance_thread ( void *  p)
staticprotected

run distance thread

void save ( CFile writer)

save kernel matrix

Parameters
writerFile object via which to save data

Definition at line 113 of file Distance.cpp.

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 314 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 436 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 431 of file SGObject.cpp.

void set_generic ( )
inherited

Definition at line 41 of file SGObject.cpp.

void set_generic ( )
inherited

Definition at line 46 of file SGObject.cpp.

void set_generic ( )
inherited

Definition at line 51 of file SGObject.cpp.

void set_generic ( )
inherited

Definition at line 56 of file SGObject.cpp.

void set_generic ( )
inherited

Definition at line 61 of file SGObject.cpp.

void set_generic ( )
inherited

Definition at line 66 of file SGObject.cpp.

void set_generic ( )
inherited

Definition at line 71 of file SGObject.cpp.

void set_generic ( )
inherited

Definition at line 76 of file SGObject.cpp.

void set_generic ( )
inherited

Definition at line 81 of file SGObject.cpp.

void set_generic ( )
inherited

Definition at line 86 of file SGObject.cpp.

void set_generic ( )
inherited

Definition at line 91 of file SGObject.cpp.

void set_generic ( )
inherited

Definition at line 96 of file SGObject.cpp.

void set_generic ( )
inherited

Definition at line 101 of file SGObject.cpp.

void set_generic ( )
inherited

Definition at line 106 of file SGObject.cpp.

void set_generic ( )
inherited

Definition at line 111 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 228 of file SGObject.cpp.

void set_global_parallel ( Parallel parallel)
inherited

set the parallel object

Parameters
parallelparallel object to use

Definition at line 241 of file SGObject.cpp.

void set_global_version ( Version version)
inherited

set the version object

Parameters
versionversion object to use

Definition at line 283 of file SGObject.cpp.

virtual void set_precompute_matrix ( bool  flag)
virtual

FIXME: precompute matrix should be dropped, handling should be via customdistance

Parameters
flagif precompute_matrix

Definition at line 297 of file Distance.h.

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 192 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 303 of file SGObject.cpp.

void update_parameter_hash ( )
virtualinherited

Updates the hash of current parameter combination

Definition at line 248 of file SGObject.cpp.

Member Data Documentation

SGIO* io
inherited

io

Definition at line 369 of file SGObject.h.

CFeatures* lhs
protected

feature vectors to occur on the left hand side

Definition at line 372 of file Distance.h.

Parameter* m_gradient_parameters
inherited

parameters wrt which we can compute gradients

Definition at line 384 of file SGObject.h.

uint32_t m_hash
inherited

Hash of parameter values

Definition at line 387 of file SGObject.h.

Parameter* m_model_selection_parameters
inherited

model selection parameters

Definition at line 381 of file SGObject.h.

Parameter* m_parameters
inherited

parameters

Definition at line 378 of file SGObject.h.

int32_t num_lhs
protected

number of feature vectors on the left hand side

Definition at line 377 of file Distance.h.

int32_t num_rhs
protected

number of feature vectors on the right hand side

Definition at line 379 of file Distance.h.

Parallel* parallel
inherited

parallel

Definition at line 372 of file SGObject.h.

bool precompute_matrix
protected

FIXME: precompute matrix should be dropped, handling should be via customdistance

Definition at line 369 of file Distance.h.

float32_t* precomputed_matrix
protected

FIXME: precompute matrix should be dropped, handling should be via customdistance

Definition at line 364 of file Distance.h.

CFeatures* rhs
protected

feature vectors to occur on the right hand side

Definition at line 374 of file Distance.h.

Version* version
inherited

version

Definition at line 375 of file SGObject.h.


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

SHOGUN Machine Learning Toolbox - Documentation