SHOGUN
v3.0.0
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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:
In the means of Shogun toolbox the distance function is defined on the 'space' of CFeatures.
Definition at line 80 of file Distance.h.
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) |
SGMatrix< float64_t > | get_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) |
CFeatures * | get_lhs () |
CFeatures * | get_rhs () |
CFeatures * | replace_rhs (CFeatures *rhs) |
CFeatures * | replace_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 | |
virtual void | remove_rhs () |
takes all necessary steps if the rhs is removed from distance matrix | |
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 CSGObject * | shallow_copy () const |
virtual CSGObject * | deep_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) |
SGIO * | get_global_io () |
void | set_global_parallel (Parallel *parallel) |
Parallel * | get_global_parallel () |
void | set_global_version (Version *version) |
Version * | get_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 bool | update_parameter_hash () |
virtual bool | equals (CSGObject *other, float64_t accuracy=0.0) |
virtual CSGObject * | clone () |
Static Public Member Functions | |
template<class T > | |
static void * | get_distance_matrix_helper (void *p) |
Public Attributes | |
SGIO * | io |
Parallel * | parallel |
Version * | version |
Parameter * | m_parameters |
Parameter * | m_model_selection_parameters |
Parameter * | m_gradient_parameters |
ParameterMap * | m_parameter_map |
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 | |
virtual TParameter * | migrate (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) |
Static Protected Member Functions | |
static void * | run_distance_thread (void *p) |
run distance thread |
Protected Attributes | |
float32_t * | precomputed_matrix |
bool | precompute_matrix |
CFeatures * | lhs |
feature vectors to occur on the left hand side | |
CFeatures * | rhs |
feature vectors to occur on the right hand side | |
int32_t | num_lhs |
int32_t | num_rhs |
CDistance | ( | ) |
default constructor
Definition at line 58 of file Distance.cpp.
init distance
lhs | features of left-hand side |
rhs | features of right-hand side |
Definition at line 64 of file Distance.cpp.
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virtual |
Definition at line 70 of file Distance.cpp.
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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.
dict | dictionary of parameters to be built. |
Definition at line 1196 of file SGObject.cpp.
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pure virtual |
cleanup distance
abstract base method
Implemented in CCustomDistance, CKernelDistance, CMahalanobisDistance, CSparseDistance< ST >, CSparseDistance< float64_t >, CStringDistance< ST >, CStringDistance< uint16_t >, CMinkowskiMetric, CEuclideanDistance, CAttenuatedEuclideanDistance, CRealDistance, CCanberraMetric, CCosineDistance, CManhattanMetric, CGeodesicMetric, CJensenMetric, CTanimotoDistance, CChiSquareDistance, CHammingWordDistance, CBrayCurtisDistance, CChebyshewMetric, CCustomMahalanobisDistance, CCanberraWordDistance, CManhattanWordDistance, and CSparseEuclideanDistance.
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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.
Definition at line 1313 of file SGObject.cpp.
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protectedpure virtual |
compute distance function for features a and b idx_{a,b} denote the index of the feature vectors in the corresponding feature object
Implemented in CCustomDistance, CMahalanobisDistance, CEuclideanDistance, CKernelDistance, CAttenuatedEuclideanDistance, CMinkowskiMetric, CCanberraMetric, CCosineDistance, CManhattanMetric, CGeodesicMetric, CJensenMetric, CTanimotoDistance, CChiSquareDistance, CHammingWordDistance, CRealDistance, CBrayCurtisDistance, CChebyshewMetric, CSparseEuclideanDistance, CCustomMahalanobisDistance, CCanberraWordDistance, and CManhattanWordDistance.
int32_t compute_row_start | ( | int64_t | offs, |
int32_t | n, | ||
bool | symmetric | ||
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compute row start offset for parallel kernel matrix computation
offs | offset |
n | number of columns |
symmetric | whether matrix is symmetric |
Definition at line 143 of file Distance.h.
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virtualinherited |
A deep copy. All the instance variables will also be copied.
Definition at line 160 of file SGObject.h.
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virtual |
get distance function for lhs feature vector a and rhs feature vector b
idx_a | feature vector a at idx_a |
idx_b | feature vector b at idx_b |
Definition at line 189 of file Distance.cpp.
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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
idx_a | feature vector a at idx_a |
idx_b | feature vector b at idx_b |
upper_bound | value above which the computation halts |
Reimplemented in CEuclideanDistance.
Definition at line 117 of file Distance.h.
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protected |
matrix precomputation
Definition at line 227 of file Distance.cpp.
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.
other | object to compare with |
accuracy | accuracy to use for comparison (optional) |
Definition at line 1217 of file SGObject.cpp.
get distance matrix
Definition at line 126 of file Distance.h.
SGMatrix<T> get_distance_matrix | ( | ) |
get distance matrix (templated)
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static |
helper for computing the kernel matrix in a parallel way
p | thread parameters |
Definition at line 266 of file Distance.cpp.
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pure virtual |
get distance type we are
abstrace base method
Implemented in CCustomDistance, CSparseDistance< ST >, CSparseDistance< float64_t >, CMahalanobisDistance, CStringDistance< ST >, CStringDistance< uint16_t >, CMinkowskiMetric, CEuclideanDistance, CKernelDistance, CAttenuatedEuclideanDistance, CRealDistance, CCanberraMetric, CCosineDistance, CManhattanMetric, CGeodesicMetric, CJensenMetric, CTanimotoDistance, CDenseDistance< ST >, CDenseDistance< float64_t >, CChiSquareDistance, CHammingWordDistance, CBrayCurtisDistance, CChebyshewMetric, CCustomMahalanobisDistance, CCanberraWordDistance, CManhattanWordDistance, and CSparseEuclideanDistance.
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pure virtual |
get feature class the distance can deal with
abstract base method
Implemented in CCustomDistance, CKernelDistance, CSparseDistance< ST >, CSparseDistance< float64_t >, CStringDistance< ST >, CStringDistance< uint16_t >, CDenseDistance< ST >, and CDenseDistance< float64_t >.
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pure virtual |
get feature type the distance can deal with
abstrace base method
Implemented in CSparseDistance< ST >, CStringDistance< ST >, CSparseDistance< ST >, CStringDistance< ST >, CSparseDistance< ST >, CStringDistance< ST >, CCustomDistance, CSparseDistance< ST >, CStringDistance< ST >, CSparseDistance< ST >, CStringDistance< ST >, CSparseDistance< ST >, CStringDistance< ST >, CSparseDistance< ST >, CMahalanobisDistance, CStringDistance< ST >, CEuclideanDistance, CKernelDistance, CAttenuatedEuclideanDistance, CDenseDistance< ST >, CSparseDistance< ST >, CSparseDistance< float64_t >, CSparseEuclideanDistance, CDenseDistance< ST >, CStringDistance< ST >, CStringDistance< uint16_t >, CDenseDistance< ST >, CDenseDistance< ST >, CRealDistance, CDenseDistance< float64_t >, CDenseDistance< ST >, CDenseDistance< ST >, CDenseDistance< ST >, and CDenseDistance< ST >.
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inherited |
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inherited |
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inherited |
CFeatures* get_lhs | ( | ) |
get left-hand side features used in distance matrix
Definition at line 194 of file Distance.h.
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inherited |
Definition at line 1100 of file SGObject.cpp.
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inherited |
Returns description of a given parameter string, if it exists. SG_ERROR otherwise
param_name | name of the parameter |
Definition at line 1124 of file SGObject.cpp.
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inherited |
Returns index of model selection parameter with provided index
param_name | name of model selection parameter |
Definition at line 1137 of file SGObject.cpp.
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pure virtualinherited |
Returns the name of the SGSerializable instance. It MUST BE the CLASS NAME without the prefixed `C'.
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 >, CDynamicArray< uint64_t >, CMultitaskKernelTreeNormalizer, CDynProg, CList, CDenseFeatures< ST >, CDenseFeatures< uint32_t >, CDenseFeatures< float64_t >, CDenseFeatures< T >, CDenseFeatures< uint16_t >, CFile, CSparseFeatures< ST >, CSparseFeatures< float64_t >, CSparseFeatures< T >, CStatistics, CSpecificityMeasure, CLibSVMFile, CPrecisionMeasure, CPlif, CRecallMeasure, CDynamicObjectArray, CCrossCorrelationMeasure, CCSVFile, CF1Measure, CLaRank, CBinaryFile, CWRACCMeasure, CTaxonomy, CStreamingSparseFeatures< T >, CBALMeasure, CBitString, CStreamingVwFeatures, CMultitaskKernelPlifNormalizer, CErrorRateMeasure, CWDSVMOcas, CMachine, CAccuracyMeasure, CStreamingFile, CRandom, CMultitaskKernelMaskNormalizer, CMemoryMappedFile< T >, CLMNNStatistics, CMemoryMappedFile< ST >, CMKL, CAlphabet, CStreamingDenseFeatures< T >, CStreamingDenseFeatures< float64_t >, CStreamingDenseFeatures< float32_t >, CCombinedDotFeatures, 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 > >, CLinearTimeMMD, CMultitaskKernelMaskPairNormalizer, CSVM, CMultitaskKernelNormalizer, CGUIClassifier, CGUIFeatures, CHashedWDFeaturesTransposed, CSimpleFile< T >, CGMM, CParameterCombination, CBinaryStream< T >, CStructuredModel, CStreamingStringFeatures< T >, CMulticlassSVM, CStateModel, CLinearHMM, CGaussian, COnlineLinearMachine, CRandomKitchenSinksDotFeatures, CVwParser, CPluginEstimate, CVowpalWabbit, CBinnedDotFeatures, CSVMOcas, CSVRLight, CHashedWDFeatures, CPlifMatrix, CCrossValidation, CImplicitWeightedSpecFeatures, CSparseMatrixOperator< T >, CCombinedFeatures, CSNPFeatures, CIOBuffer, CWDFeatures, CCrossValidationMulticlassStorage, CHashedDenseFeatures< ST >, CLeastAngleRegression, CQuadraticTimeMMD, CTwoStateModel, CGUIKernel, CHMSVMModel, CLossFunction, CKNN, CRandomFourierGaussPreproc, CHashedSparseFeatures< ST >, CMKLMulticlass, CExplicitSpecFeatures, CLibLinearMTL, CModelSelectionParameters, CGUIHMM, CHashedDocDotFeatures, CJacobiEllipticFunctions, COnlineSVMSGD, CPositionalPWM, CZeroMeanCenterKernelNormalizer, CSparsePolyFeatures, CCplex, CSqrtDiagKernelNormalizer, CScatterKernelNormalizer, CRationalApproximation, CStochasticProximityEmbedding, CLatentModel, CGMNPLib, CDixonQTestRejectionStrategy, CLibLinear, CMulticlassMachine, CTableFactorType, CSVMSGD, CVwCacheReader, CLBPPyrDotFeatures, CRidgeKernelNormalizer, CHSIC, CLinearMachine, CTestStatistic, CTime, CSGDQN, CSNPStringKernel, CMatrixFeatures< ST >, CWeightedCommWordStringKernel, CHingeLoss, CQPBSVMLib, CSerializableAsciiFile, CSquaredLoss, CCustomKernel, CFactor, CPlifArray, CStreamingVwFile, CMulticlassLabels, CHash, CStreamingHashedDocDotFeatures, CQDA, CKernelRidgeRegression, CCustomDistance, CWeightedDegreeStringKernel, CKMeans, CBaggingMachine, CTOPFeatures, CDiceKernelNormalizer, CMultitaskKernelMklNormalizer, CTask, CVwEnvironment, CBinaryLabels, CMAPInferImpl, CDomainAdaptationSVMLinear, CLDA, CMCLDA, CWeightedDegreePositionStringKernel, CBesselKernel, CTanimotoKernelNormalizer, CStreamingHashedDenseFeatures< ST >, CStreamingHashedSparseFeatures< ST >, CAvgDiagKernelNormalizer, CVarianceKernelNormalizer, CCircularBuffer, CKernelTwoSampleTestStatistic, COperatorFunction< T >, COperatorFunction< float64_t >, CHierarchical, CFKFeatures, CSpectrumMismatchRBFKernel, CMulticlassModel, CCombinedKernel, CSparseSpatialSampleStringKernel, CVwRegressor, CFactorGraphLabels, CDotKernel, CGaussianKernel, CCommWordStringKernel, CSet< T >, CDenseMatrixOperator< T >, CSequenceLabels, CDenseMatrixOperator< float64_t >, CTwoDistributionsTestStatistic, CNode, CContingencyTableEvaluation, CPolyFeatures, CStreamingAsciiFile, CLibSVR, COnlineLibLinear, CChi2Kernel, CPyramidChi2, CSignal, CIntegration, CLPBoost, CSalzbergWordStringKernel, CStructuredLabels, CSquaredHingeLoss, CPCA, CNewtonSVM, CHashedDocConverter, CCompressor, CIterativeLinearSolver< T, ST >, CIterativeLinearSolver< float64_t, float64_t >, CIterativeLinearSolver< complex128_t, float64_t >, CIterativeLinearSolver< T, T >, CSVMLin, CVwLearner, CLocallyLinearEmbedding, CDistanceKernel, CCommUlongStringKernel, CScatterSVM, CHomogeneousKernelMap, CVwNativeCacheReader, CHistogram, CGaussianShiftKernel, CMahalanobisDistance, CAttributeFeatures, CRandomFourierDotFeatures, CFirstElementKernelNormalizer, CGCArray< T >, CMap< K, T >, CLogLoss, CLogLossMargin, CSmoothHingeLoss, CMap< TParameter *, CSGObject * >, CMap< TParameter *, SGVector< float64_t > >, CGNPPLib, CLatentLabels, CLinearRidgeRegression, CSphericalKernel, CSpectrumRBFKernel, CIndexBlockTree, CSegmentLoss, CDomainAdaptationSVM, CKernelDistance, CEigenSolver, CMulticlassSOLabels, CLPM, CCircularKernel, CPolyMatchStringKernel, CSimpleLocalityImprovedStringKernel, CGaussianDistribution, CStreamingFileFromFeatures, CStreamingVwCacheFile, COligoStringKernel, CLanczosEigenSolver, CMultidimensionalScaling, CDataGenerator, CANOVAKernel, CConstKernel, CDiagKernel, CMulticlassMultipleOutputLabels, CKernelPCA, CMultitaskClusteredLogisticRegression, CEmbeddingConverter, CEuclideanDistance, CWeightedMajorityVote, CMulticlassOVREvaluation, CPolyKernel, CPolyMatchWordStringKernel, CTraceSampler, CNearestCentroid, CStreamingFileFromDenseFeatures< T >, CStreamingFileFromSparseFeatures< T >, CStreamingFileFromStringFeatures< T >, CProductKernel, CSparseKernel< ST >, CGaussianMatchStringKernel, CTStudentKernel, CGaussianProcessRegression, CDiffusionMaps, CFixedDegreeStringKernel, CStringKernel< ST >, CTensorProductPairKernel, CDistanceMachine, CGaussianNaiveBayes, CMulticlassOneVsRestStrategy, CStringKernel< uint16_t >, CStringKernel< char >, CStringKernel< uint64_t >, CLaplacianEigenmaps, CCauchyKernel, CLogKernel, CPowerKernel, CRationalQuadraticKernel, CWaveKernel, CWaveletKernel, CKernelIndependenceTestStatistic, MKLMulticlassGradient, CMinkowskiMetric, CExponentialKernel, CAttenuatedEuclideanDistance, CParser, CDistantSegmentsKernel, CKernelMachine, CInverseMultiQuadricKernel, CLocalityImprovedStringKernel, CMatchWordStringKernel, CRegulatoryModulesStringKernel, CFFDiag, CJADiag, CJADiagOrth, CAUCKernel, CHistogramIntersectionKernel, CSigmoidKernel, CJediDiag, CQDiag, CUWedge, CMMDKernelSelectionCombOpt, CMultiquadricKernel, CExactInferenceMethod, CLocalAlignmentStringKernel, CLogRationalApproximationIndividual, CICAConverter, CMulticlassAccuracy, CGaussianARDKernel, CGaussianShortRealKernel, CStructuredOutputMachine, CMatrixOperator< T >, CMMDKernelSelectionCombMaxL2, CMatrixOperator< float64_t >, CPerceptron, CSplineKernel, CLinearOperator< T >, CCGMShiftedFamilySolver, CIterativeShiftedLinearFamilySolver< T, ST >, CLogRationalApproximationCGM, CDimensionReductionPreprocessor, CLinearOperator< float64_t >, CLinearOperator< complex128_t >, CIterativeShiftedLinearFamilySolver< float64_t, complex128_t >, CGHMM, CHistogramWordStringKernel, CDelimiterTokenizer, CLogDetEstimator, CTaskTree, CProbabilityDistribution, CFITCInferenceMethod, CLaplacianInferenceMethod, CMultitaskL12LogisticRegression, CMultitaskROCEvaluation, CGUIConverter, CCanberraMetric, CCosineDistance, CManhattanMetric, CJensenShannonKernel, CLinearKernel, CGeodesicMetric, CJensenMetric, CTanimotoDistance, CIdentityKernelNormalizer, CLinearStringKernel, CDecompressString< ST >, CDualLibQPBMSOSVM, CGUILabels, CSOBI, CKernelLocallyLinearEmbedding, CLabelsFactory, CMMDKernelSelection, CMMDKernelSelectionComb, CMMDKernelSelectionMedian, MKLMulticlassGLPK, CFFSep, CChiSquareDistance, CHammingWordDistance, CJobResultAggregator, CNGramTokenizer, CLinearStructuredOutputMachine, CRandomSearchModelSelection, CMulticlassOneVsOneStrategy, CLeastSquaresRegression, CAveragedPerceptron, CVwNativeCacheWriter, CJediSep, CUWedgeSep, CSparseDistance< ST >, CCrossValidationResult, CLatentFeatures, CDenseMatrixExactLog, CLibLinearRegression, CMMDKernelSelectionOpt, CGUIPluginEstimate, CSparseDistance< float64_t >, CVwAdaptiveLearner, CBrayCurtisDistance, CChebyshewMetric, CFactorGraphFeatures, CLineReader, CRegressionLabels, MKLMulticlassOptimizationBase, CVwNonAdaptiveLearner, CSparseEuclideanDistance, CRealFileFeatures, CLinearARDKernel, CIndependentJob, CPNorm, CStringDistance< ST >, CEPInferenceMethod, CMulticlassStrategy, CRescaleFeatures, CMAPInference, CStringDistance< uint16_t >, CWeightedDegreeRBFKernel, CDirectLinearSolverComplex, CIndividualJobResultAggregator, CECOCRandomSparseEncoder, CLogPlusOne, CGradientCriterion, CScalarResult< T >, CRationalApproximationCGMJob, CGMNPSVM, CNormOne, CMultitaskLogisticRegression, CFastICA, CFactorGraphObservation, CLinearLatentMachine, CRationalApproximationIndividualJob, CMultitaskTraceLogisticRegression, CGUIDistance, CLibSVM, CStringFileFeatures< ST >, CLatentSVM, CLinearMulticlassMachine, CConjugateOrthogonalCGSolver, CSumOne, CJade, CCanberraWordDistance, CManhattanWordDistance, CCrossValidationOutput, CGradientModelSelection, CECOCDiscriminantEncoder, CSortWordString, CTaskGroup, CGUIPreprocessor, CFeatureBlockLogisticRegression, CStudentsTLikelihood, CDenseExactLogJob, CPruneVarSubMean, CIntronList, CStructuredAccuracy, CStoreVectorAggregator< T >, CLMNN, CMulticlassLibLinear, CSortUlongString, CSequence, CResultSet, CStoreVectorAggregator< complex128_t >, CIsomap, CMeanSquaredError, CMeanSquaredLogError, CLatentSOSVM, CIndependentComputationEngine, CIndexBlock, CThresholdRejectionStrategy, CRealNumber, CSVMLightOneClass, CLinearLocalTangentSpaceAlignment, CNeighborhoodPreservingEmbedding, CMeanAbsoluteError, CDummyFeatures, CVectorResult< T >, CListElement, CCCSOSVM, CHessianLocallyLinearEmbedding, CDenseDistance< ST >, CRealDistance, CStoreScalarAggregator< T >, CIndexBlockGroup, CConjugateGradientSolver, CSparsePreprocessor< ST >, CMMDKernelSelectionMax, CMultitaskLeastSquaresRegression, CDenseDistance< float64_t >, CLocalTangentSpaceAlignment, CClusteringAccuracy, CClusteringMutualInformation, CMeanShiftDataGenerator, CGaussianLikelihood, CKernelStructuredOutputMachine, CMultitaskLinearMachine, CCustomMahalanobisDistance, CCombinationRule, CGaussianProcessMachine, CStringPreprocessor< ST >, CStringPreprocessor< uint16_t >, CStringPreprocessor< uint64_t >, CSubsetStack, CDirectEigenSolver, CLinearSolver< T, ST >, CGridSearchModelSelection, CVwConditionalProbabilityTree, CLinearSolver< float64_t, float64_t >, CLinearSolver< complex128_t, float64_t >, CLinearSolver< T, T >, CLocalityPreservingProjections, CMajorityVote, CFactorGraphModel, CMeanRule, CGradientEvaluation, CSerialComputationEngine, CKernelMulticlassMachine, CNormalSampler, CMulticlassLibSVM, CMKLRegression, CFactorDataSource, CFactorGraph, CDomainAdaptationMulticlassLibLinear, CGaussianBlobsDataGenerator, CECOCEncoder, CMulticlassTreeGuidedLogisticRegression, CKernelMeanMatching, CTaskRelation, CROCEvaluation, CSubset, CIndexBlockRelation, CDirectSparseLinearSolver, CMulticlassLogisticRegression, CBalancedConditionalProbabilityTree, CTreeMachineNode< T >, CFactorType, CTreeMachineNode< ConditionalProbabilityTreeNodeData >, CTreeMachineNode< RelaxedTreeNodeData >, CTreeMachineNode< VwConditionalProbabilityTreeNodeData >, CMKLClassification, CMKLOneClass, CGPBTSVM, CLibSVMOneClass, CGradientResult, CECOCIHDDecoder, CConditionalProbabilityTree, CRelaxedTree, CGNPPSVM, CMPDSVM, CProbitLikelihood, CECOCRandomDenseEncoder, CMulticlassOCAS, CShareBoost, CTreeMachine< T >, CTreeMachine< ConditionalProbabilityTreeNodeData >, CTreeMachine< RelaxedTreeNodeData >, CTreeMachine< VwConditionalProbabilityTreeNodeData >, CStratifiedCrossValidationSplitting, CPRCEvaluation, CGUIMath, CGUITime, CCrossValidationSplitting, CLogitLikelihood, CSparseInverseCovariance, CDisjointSet, CTDistributedStochasticNeighborEmbedding, CDenseSubsetFeatures< ST >, CECOCForestEncoder, CFactorAnalysis, CManifoldSculpting, CJobResult, CCrossValidationPrintOutput, CECOCAEDDecoder, CECOCDecoder, CCrossValidationMKLStorage, CNativeMulticlassMachine, CFunction, CECOCEDDecoder, CECOCStrategy, CData, CZeroMean, CConverter, CECOCSimpleDecoder, SerializableAsciiReader00, CBaseMulticlassMachine, CECOCLLBDecoder, CStructuredData, CECOCHDDecoder, CECOCOVOEncoder, CECOCOVREncoder, CRandomConditionalProbabilityTree, and CRejectionStrategy.
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virtual |
get number of vectors of lhs features
Reimplemented in CCustomDistance.
Definition at line 282 of file Distance.h.
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virtual |
get number of vectors of rhs features
Reimplemented in CCustomDistance.
Definition at line 291 of file Distance.h.
bool get_precompute_matrix | ( | ) |
FIXME: precompute matrix should be dropped, handling should be via customdistance
Definition at line 260 of file Distance.h.
CFeatures* get_rhs | ( | ) |
get right-hand side features used in distance matrix
Definition at line 200 of file Distance.h.
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virtual |
test whether features have been assigned to lhs and rhs
Reimplemented in CCustomDistance.
Definition at line 300 of file Distance.h.
init distance
make sure to check that your distance can deal with the supplied features (!)
lhs | features of left-hand side |
rhs | features of right-hand side |
Reimplemented in CCustomDistance, CMahalanobisDistance, CKernelDistance, CMinkowskiMetric, CEuclideanDistance, CAttenuatedEuclideanDistance, CCanberraMetric, CCosineDistance, CManhattanMetric, CGeodesicMetric, CJensenMetric, CTanimotoDistance, CChiSquareDistance, CHammingWordDistance, CBrayCurtisDistance, CChebyshewMetric, CCanberraWordDistance, CManhattanWordDistance, CSparseEuclideanDistance, CStringDistance< ST >, CStringDistance< uint16_t >, CDenseDistance< ST >, CDenseDistance< float64_t >, CRealDistance, CSparseDistance< ST >, and CSparseDistance< float64_t >.
Definition at line 78 of file Distance.cpp.
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virtualinherited |
If the SGSerializable is a class template then TRUE will be returned and GENERIC is set to the type of the generic.
generic | set to the type of the generic if returning TRUE |
Definition at line 268 of file SGObject.cpp.
bool lhs_equals_rhs | ( | ) |
test whether features on lhs and rhs are the same
Definition at line 309 of file Distance.h.
void load | ( | CFile * | loader | ) |
load the kernel matrix
loader | File object via which to load data |
Definition at line 107 of file Distance.cpp.
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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)
file_version | parameter version of the file |
current_version | version from which mapping begins (you want to use Version::get_version_parameter() for this in most cases) |
file | file to load from |
prefix | prefix for members |
Definition at line 673 of file SGObject.cpp.
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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
param_info | information of parameter |
file_version | parameter version of the file, must be <= provided parameter version |
file | file to load from |
prefix | prefix for members |
Definition at line 514 of file SGObject.cpp.
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virtualinherited |
Load this object from file. If it will fail (returning FALSE) then this object will contain inconsistent data and should not be used!
file | where to load from |
prefix | prefix for members |
param_version | (optional) a parameter version different to (this is mainly for testing, better do not use) |
Definition at line 345 of file SGObject.cpp.
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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.
ShogunException | Will be thrown if an error occurres. |
Reimplemented in CKernel, CWeightedDegreePositionStringKernel, CList, CAlphabet, CLinearHMM, CGaussianKernel, CInverseMultiQuadricKernel, CCircularKernel, and CExponentialKernel.
Definition at line 1029 of file SGObject.cpp.
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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.
ShogunException | Will be thrown if an error occurres. |
Reimplemented in CDynamicArray< T >, CDynamicArray< float64_t >, CDynamicArray< float32_t >, CDynamicArray< int32_t >, CDynamicArray< char >, CDynamicArray< bool >, CDynamicArray< uint64_t >, and CDynamicObjectArray.
Definition at line 1024 of file SGObject.cpp.
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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
param_base | set of TParameter instances that are mapped to the provided target parameter infos |
base_version | version of the parameter base |
target_param_infos | set of SGParamInfo instances that specify the target parameter base |
Definition at line 711 of file SGObject.cpp.
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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
param_base | set of TParameter instances to use for migration |
target | parameter info for the resulting TParameter |
Definition at line 918 of file SGObject.cpp.
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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)
param_base | set of TParameter instances to use for migration |
target | parameter info for the resulting TParameter |
replacement | (used as output) here the TParameter instance which is returned by migration is created into |
to_migrate | the only source that is used for migration |
old_name | with this parameter, a name change may be specified |
Definition at line 858 of file SGObject.cpp.
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inherited |
prints all parameter registered for model selection and their type
Definition at line 1076 of file SGObject.cpp.
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virtualinherited |
prints registered parameters out
prefix | prefix for members |
Definition at line 280 of file SGObject.cpp.
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virtual |
takes all necessary steps if the lhs is removed from distance matrix
Definition at line 130 of file Distance.cpp.
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virtual |
remove lhs and rhs from distance
Definition at line 119 of file Distance.cpp.
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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.
replace left-hand side features used in distance matrix
make sure to check that your distance can deal with the supplied features (!)
lhs | features of right-hand side |
Definition at line 167 of file Distance.cpp.
replace right-hand side features used in distance matrix
make sure to check that your distance can deal with the supplied features (!)
rhs | features of right-hand side |
Definition at line 145 of file Distance.cpp.
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staticprotected |
run distance thread
void save | ( | CFile * | writer | ) |
save kernel matrix
writer | File object via which to save data |
Definition at line 113 of file Distance.cpp.
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virtualinherited |
Save this object to file.
file | where to save the object; will be closed during returning if PREFIX is an empty string. |
prefix | prefix for members |
param_version | (optional) a parameter version different to (this is mainly for testing, better do not use) |
Definition at line 286 of file SGObject.cpp.
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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.
ShogunException | Will be thrown if an error occurres. |
Reimplemented in CKernel.
Definition at line 1039 of file SGObject.cpp.
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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.
ShogunException | Will be thrown if an error occurres. |
Reimplemented in CKernel, CDynamicArray< T >, CDynamicArray< float64_t >, CDynamicArray< float32_t >, CDynamicArray< int32_t >, CDynamicArray< char >, CDynamicArray< bool >, CDynamicArray< uint64_t >, and CDynamicObjectArray.
Definition at line 1034 of file SGObject.cpp.
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inherited |
set generic type to T
Definition at line 41 of file SGObject.cpp.
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inherited |
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inherited |
set the parallel object
parallel | parallel object to use |
Definition at line 220 of file SGObject.cpp.
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inherited |
set the version object
version | version object to use |
Definition at line 255 of file SGObject.cpp.
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virtual |
FIXME: precompute matrix should be dropped, handling should be via customdistance
flag | if precompute_matrix |
Definition at line 267 of file Distance.h.
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virtualinherited |
A shallow copy. All the SGObject instance variables will be simply assigned and SG_REF-ed.
Reimplemented in CGaussianKernel.
Definition at line 151 of file SGObject.h.
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inherited |
unset generic type
this has to be called in classes specializing a template class
Definition at line 275 of file SGObject.cpp.
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virtualinherited |
Updates the hash of current parameter combination.
Definition at line 227 of file SGObject.cpp.
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inherited |
io
Definition at line 514 of file SGObject.h.
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protected |
feature vectors to occur on the left hand side
Definition at line 342 of file Distance.h.
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inherited |
parameters wrt which we can compute gradients
Definition at line 529 of file SGObject.h.
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inherited |
Hash of parameter values
Definition at line 535 of file SGObject.h.
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inherited |
model selection parameters
Definition at line 526 of file SGObject.h.
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inherited |
map for different parameter versions
Definition at line 532 of file SGObject.h.
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inherited |
parameters
Definition at line 523 of file SGObject.h.
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protected |
number of feature vectors on the left hand side
Definition at line 347 of file Distance.h.
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protected |
number of feature vectors on the right hand side
Definition at line 349 of file Distance.h.
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inherited |
parallel
Definition at line 517 of file SGObject.h.
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protected |
FIXME: precompute matrix should be dropped, handling should be via customdistance
Definition at line 339 of file Distance.h.
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protected |
FIXME: precompute matrix should be dropped, handling should be via customdistance
Definition at line 334 of file Distance.h.
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protected |
feature vectors to occur on the right hand side
Definition at line 344 of file Distance.h.
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inherited |
version
Definition at line 520 of file SGObject.h.