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CStreamingDotFeatures Class Reference

Detailed Description

Streaming features that support dot products among other operations.

DotFeatures support the following operations:

Definition at line 47 of file StreamingDotFeatures.h.

Inheritance diagram for CStreamingDotFeatures:
Inheritance graph
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Public Member Functions

 CStreamingDotFeatures ()
 CStreamingDotFeatures (CStreamingFile *file, bool is_labelled, int32_t size)
 CStreamingDotFeatures (CDotFeatures *dot_features, float64_t *lab=NULL)
virtual ~CStreamingDotFeatures ()
virtual float32_t dot (CStreamingDotFeatures *df)=0
virtual float32_t dense_dot (const float32_t *vec2, int32_t vec2_len)=0
virtual void dense_dot_range (float32_t *output, float32_t *alphas, float32_t *vec, int32_t dim, float32_t b, int32_t num_vec=0)
virtual void add_to_dense_vec (float32_t alpha, float32_t *vec2, int32_t vec2_len, bool abs_val=false)=0
virtual void expand_if_required (float32_t *&vec, int32_t &len)
virtual void expand_if_required (float64_t *&vec, int32_t &len)
virtual int32_t get_dim_feature_space () const =0
virtual void * get_feature_iterator ()
virtual int32_t get_nnz_features_for_vector ()
virtual bool get_next_feature (int32_t &index, float32_t &value, void *iterator)
virtual void free_feature_iterator (void *iterator)
void set_read_functions ()
virtual void set_vector_reader ()=0
virtual void set_vector_and_label_reader ()=0
virtual void start_parser ()=0
virtual void end_parser ()=0
virtual float64_t get_label ()=0
virtual bool get_next_example ()=0
virtual void release_example ()=0
virtual int32_t get_num_features ()=0
virtual bool get_has_labels ()
virtual bool is_seekable ()
virtual void reset_stream ()
virtual CFeaturesget_streamed_features (index_t num_elements)
virtual CFeaturesduplicate () const =0
virtual EFeatureType get_feature_type () const =0
virtual EFeatureClass get_feature_class () const =0
virtual void add_preprocessor (CPreprocessor *p)
virtual void del_preprocessor (int32_t num)
CPreprocessorget_preprocessor (int32_t num) const
void set_preprocessed (int32_t num)
bool is_preprocessed (int32_t num) const
int32_t get_num_preprocessed () const
int32_t get_num_preprocessors () const
void clean_preprocessors ()
void list_preprocessors ()
int32_t get_cache_size () const
virtual int32_t get_num_vectors () const =0
virtual bool reshape (int32_t num_features, int32_t num_vectors)
void list_feature_obj () const
virtual void load (CFile *loader)
virtual void save (CFile *writer)
bool check_feature_compatibility (CFeatures *f) const
bool has_property (EFeatureProperty p) const
void set_property (EFeatureProperty p)
void unset_property (EFeatureProperty p)
virtual CFeaturescreate_merged_copy (CList *others)
virtual CFeaturescreate_merged_copy (CFeatures *other)
virtual void add_subset (SGVector< index_t > subset)
virtual void add_subset_in_place (SGVector< index_t > subset)
virtual void remove_subset ()
virtual void remove_all_subsets ()
virtual CSubsetStackget_subset_stack ()
virtual void subset_changed_post ()
virtual CFeaturescopy_subset (SGVector< index_t > indices)
virtual CFeaturescopy_dimension_subset (SGVector< index_t > dims)
virtual CSGObjectshallow_copy () const
virtual CSGObjectdeep_copy () const
virtual const char * get_name () const =0
virtual bool is_generic (EPrimitiveType *generic) const
template<class T >
void set_generic ()
void unset_generic ()
virtual void print_serializable (const char *prefix="")
virtual bool save_serializable (CSerializableFile *file, const char *prefix="", int32_t param_version=Version::get_version_parameter())
virtual bool load_serializable (CSerializableFile *file, const char *prefix="", int32_t param_version=Version::get_version_parameter())
DynArray< TParameter * > * load_file_parameters (const SGParamInfo *param_info, int32_t file_version, CSerializableFile *file, const char *prefix="")
DynArray< TParameter * > * load_all_file_parameters (int32_t file_version, int32_t current_version, CSerializableFile *file, const char *prefix="")
void map_parameters (DynArray< TParameter * > *param_base, int32_t &base_version, DynArray< const SGParamInfo * > *target_param_infos)
void set_global_io (SGIO *io)
SGIOget_global_io ()
void set_global_parallel (Parallel *parallel)
Parallelget_global_parallel ()
void set_global_version (Version *version)
Versionget_global_version ()
SGStringList< char > get_modelsel_names ()
void print_modsel_params ()
char * get_modsel_param_descr (const char *param_name)
index_t get_modsel_param_index (const char *param_name)
void build_gradient_parameter_dictionary (CMap< TParameter *, CSGObject * > *dict)
virtual void update_parameter_hash ()
virtual bool parameter_hash_changed ()
virtual bool equals (CSGObject *other, float64_t accuracy=0.0, bool tolerant=false)
virtual CSGObjectclone ()

Public Attributes

SGIOio
Parallelparallel
Versionversion
Parameterm_parameters
Parameterm_model_selection_parameters
Parameterm_gradient_parameters
ParameterMapm_parameter_map
uint32_t m_hash

Protected Member Functions

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

Protected Attributes

bool has_labels
 Whether examples are labelled or not.
CStreamingFileworking_file
 The StreamingFile object to read from.
bool seekable
 Whether the stream is seekable.
CSubsetStackm_subset_stack

Constructor & Destructor Documentation

Constructor

Definition at line 14 of file StreamingDotFeatures.cpp.

CStreamingDotFeatures ( CStreamingFile file,
bool  is_labelled,
int32_t  size 
)

Constructor with input information passed.

Parameters
fileCStreamingFile to take input from.
is_labelledWhether examples are labelled or not.
sizeNumber of examples to be held in the parser's "ring".
CStreamingDotFeatures ( CDotFeatures dot_features,
float64_t lab = NULL 
)

Constructor taking a CDotFeatures object and optionally, labels, as args.

The derived class should implement it so that the Streaming*Features class uses the DotFeatures object as the input, getting examples one by one from the DotFeatures object (and labels, if applicable).

Parameters
dot_featuresCDotFeatures object
lablabels (optional)

Definition at line 19 of file StreamingDotFeatures.cpp.

~CStreamingDotFeatures ( )
virtual

Definition at line 26 of file StreamingDotFeatures.cpp.

Member Function Documentation

void add_preprocessor ( CPreprocessor p)
virtualinherited

add preprocessor

Parameters
ppreprocessor to set

Definition at line 85 of file Features.cpp.

void add_subset ( SGVector< index_t subset)
virtualinherited

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

Calls subset_changed_post() afterwards

Parameters
subsetsubset of indices to add

Reimplemented in CCombinedFeatures.

Definition at line 310 of file Features.cpp.

void add_subset_in_place ( SGVector< index_t subset)
virtualinherited

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

Calls subset_changed_post() afterwards

Parameters
subsetsubset of indices to replace the latest one with.

Definition at line 316 of file Features.cpp.

virtual void add_to_dense_vec ( float32_t  alpha,
float32_t vec2,
int32_t  vec2_len,
bool  abs_val = false 
)
pure virtual

add current vector multiplied with alpha to dense vector, 'vec'

Parameters
alphascalar alpha
vec2real valued vector to add to
vec2_lenlength of vector
abs_valif true add the absolute value

Implemented in CStreamingVwFeatures, CStreamingSparseFeatures< T >, CStreamingDenseFeatures< T >, CStreamingDenseFeatures< float64_t >, CStreamingDenseFeatures< float32_t >, CStreamingHashedDocDotFeatures, CStreamingHashedDenseFeatures< ST >, and CStreamingHashedSparseFeatures< ST >.

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 1243 of file SGObject.cpp.

bool check_feature_compatibility ( CFeatures f) const
inherited

check feature compatibility

Parameters
ffeatures to check for compatibility
Returns
if features are compatible

Definition at line 283 of file Features.cpp.

void clean_preprocessors ( )
inherited

clears all preprocs

Definition at line 116 of file Features.cpp.

CSGObject * clone ( )
virtualinherited

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

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

Definition at line 1360 of file SGObject.cpp.

CFeatures * copy_dimension_subset ( SGVector< index_t dims)
virtualinherited

Creates a new CFeatures instance containing only the dimensions of the feature vector which are specified by the provided indices.

This method is needed for feature selection tasks NOT IMPLEMENTED!

Parameters
dimsindices of feature dimensions to copy
Returns
new CFeatures instance with copies of specified features

Reimplemented in CDenseFeatures< ST >, CDenseFeatures< uint32_t >, CDenseFeatures< float64_t >, CDenseFeatures< T >, and CDenseFeatures< uint16_t >.

Definition at line 348 of file Features.cpp.

CFeatures * copy_subset ( SGVector< index_t indices)
virtualinherited

Creates a new CFeatures instance containing copies of the elements which are specified by the provided indices.

This method is needed for a KernelMachine to store its model data. NOT IMPLEMENTED!

Parameters
indicesindices of feature elements to copy
Returns
new CFeatures instance with copies of feature data

Reimplemented in CStringFeatures< ST >, CStringFeatures< T >, CStringFeatures< uint8_t >, CStringFeatures< char >, CStringFeatures< uint16_t >, CSparseFeatures< ST >, CSparseFeatures< float64_t >, CSparseFeatures< T >, CDenseFeatures< ST >, CDenseFeatures< uint32_t >, CDenseFeatures< float64_t >, CDenseFeatures< T >, CDenseFeatures< uint16_t >, and CCombinedFeatures.

Definition at line 340 of file Features.cpp.

virtual CFeatures* create_merged_copy ( CList others)
virtualinherited

Takes a list of feature instances and returns a new instance being a concatenation of a copy of this instace's data and the given instancess data. Note that the feature types have to be equal.

NOT IMPLEMENTED!

Parameters
otherslist of feature objects to append
Returns
new feature object which contains copy of data of this instance and given ones

Reimplemented in CDenseFeatures< ST >, CDenseFeatures< uint32_t >, CDenseFeatures< float64_t >, CDenseFeatures< T >, and CDenseFeatures< uint16_t >.

Definition at line 235 of file Features.h.

virtual CFeatures* create_merged_copy ( CFeatures other)
virtualinherited

Convenience method for method with same name and list as parameter.

NOT IMPLEMENTED!

Parameters
otherfeature object to append
Returns
new feature object which contains copy of data of this instance and of given one

Reimplemented in CDenseFeatures< ST >, CDenseFeatures< uint32_t >, CDenseFeatures< float64_t >, CDenseFeatures< T >, CDenseFeatures< uint16_t >, and CCombinedFeatures.

Definition at line 249 of file Features.h.

CSGObject * deep_copy ( ) const
virtualinherited

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

Definition at line 200 of file SGObject.cpp.

void del_preprocessor ( int32_t  num)
virtualinherited

delete preprocessor from list

Parameters
numindex of preprocessor in list

Definition at line 122 of file Features.cpp.

virtual float32_t dense_dot ( const float32_t vec2,
int32_t  vec2_len 
)
pure virtual
void dense_dot_range ( float32_t output,
float32_t alphas,
float32_t vec,
int32_t  dim,
float32_t  b,
int32_t  num_vec = 0 
)
virtual

Compute the dot product for all vectors. This function makes use of dense_dot alphas[i] * sparse[i]^T * w + b

Parameters
outputresult for the given vector range
alphasscalars to multiply with, may be NULL
vecdense vector to compute dot product with
dimlength of the dense vector
bbias
num_vecnumber of vectors to operate on (indices 0 to num_vec-1)

If num_vec == 0 or left to its default value, the function attempts to return dot product for all vectors. However, the given output vector must be preallocated!

note that the result will be written to output[0...(num_vec-1)] except when num_vec = 0

Definition at line 30 of file StreamingDotFeatures.cpp.

virtual float32_t dot ( CStreamingDotFeatures df)
pure virtual

compute dot product between vectors of two StreamingDotFeatures objects.

Parameters
dfStreamingDotFeatures (of same kind) to compute dot product with

Implemented in CStreamingVwFeatures, CStreamingSparseFeatures< T >, CStreamingDenseFeatures< T >, CStreamingDenseFeatures< float64_t >, CStreamingDenseFeatures< float32_t >, CStreamingHashedDocDotFeatures, CStreamingHashedDenseFeatures< ST >, and CStreamingHashedSparseFeatures< ST >.

virtual CFeatures* duplicate ( ) const
pure virtualinherited
virtual void end_parser ( )
pure virtualinherited
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 1264 of file SGObject.cpp.

void expand_if_required ( float32_t *&  vec,
int32_t &  len 
)
virtual

Expand the vector passed so that it its length is equal to the dimensionality of the features. The previous values are kept intact through realloc, and the new ones are set to zero.

Parameters
vecfloat32_t* vector
lenlength of the vector

Reimplemented in CStreamingVwFeatures.

Definition at line 53 of file StreamingDotFeatures.cpp.

void expand_if_required ( float64_t *&  vec,
int32_t &  len 
)
virtual

Expand the vector passed so that it its length is equal to the dimensionality of the features. The previous values are kept intact through realloc, and the new ones are set to zero.

Parameters
vecfloat64_t* vector
lenlength of the vector

Reimplemented in CStreamingVwFeatures.

Definition at line 64 of file StreamingDotFeatures.cpp.

void free_feature_iterator ( void *  iterator)
virtual

clean up iterator call this function with the iterator returned by get_first_feature

Parameters
iteratoras returned by get_first_feature

Definition at line 93 of file StreamingDotFeatures.cpp.

int32_t get_cache_size ( ) const
inherited

get cache size

Returns
cache size

Definition at line 160 of file Features.cpp.

virtual int32_t get_dim_feature_space ( ) const
pure virtual

obtain the dimensionality of the feature space

(not mix this up with the dimensionality of the input space, usually obtained via get_num_features())

Returns
dimensionality

Implemented in CStreamingVwFeatures, CStreamingSparseFeatures< T >, CStreamingDenseFeatures< T >, CStreamingDenseFeatures< float64_t >, CStreamingDenseFeatures< float32_t >, CStreamingHashedDocDotFeatures, CStreamingHashedDenseFeatures< ST >, and CStreamingHashedSparseFeatures< ST >.

virtual EFeatureClass get_feature_class ( ) const
pure virtualinherited
void * get_feature_iterator ( )
virtual

iterate over the non-zero features

call get_feature_iterator first, followed by get_next_feature and free_feature_iterator to cleanup

Returns
feature iterator (to be passed to get_next_feature)

Definition at line 75 of file StreamingDotFeatures.cpp.

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

get the io object

Returns
io object

Definition at line 237 of file SGObject.cpp.

Parallel * get_global_parallel ( )
inherited

get the parallel object

Returns
parallel object

Definition at line 278 of file SGObject.cpp.

Version * get_global_version ( )
inherited

get the version object

Returns
version object

Definition at line 291 of file SGObject.cpp.

bool get_has_labels ( )
virtualinherited

Return whether the examples are labelled or not.

Returns
true if labelled, else false

Definition at line 35 of file StreamingFeatures.cpp.

virtual float64_t get_label ( )
pure virtualinherited
SGStringList< char > get_modelsel_names ( )
inherited
Returns
vector of names of all parameters which are registered for model selection

Definition at line 1135 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 1159 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 1172 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, CStatistics, CSparseFeatures< ST >, CSparseFeatures< float64_t >, CSparseFeatures< T >, CSpecificityMeasure, CPrecisionMeasure, CPlif, CRecallMeasure, CDynamicObjectArray, CCrossCorrelationMeasure, CF1Measure, CCSVFile, CProtobufFile, CBinaryFile, CLaRank, CWRACCMeasure, CRBM, CTaxonomy, CBALMeasure, CBitString, CStreamingVwFeatures, CLibSVMFile, CStreamingSparseFeatures< T >, CMultitaskKernelPlifNormalizer, CErrorRateMeasure, CWDSVMOcas, CMachine, CNeuralLayer, CAccuracyMeasure, CStreamingFile, CQuadraticTimeMMD, CRandom, CStreamingMMD, CMultitaskKernelMaskNormalizer, CMemoryMappedFile< T >, CMemoryMappedFile< ST >, CAlphabet, CMKL, CStreamingDenseFeatures< T >, CLMNNStatistics, CStructuredModel, CStreamingDenseFeatures< float64_t >, CStreamingDenseFeatures< float32_t >, CCombinedDotFeatures, CFeatureSelection< ST >, CFeatureSelection< float64_t >, CGUIStructure, CCache< T >, CCache< SGSparseVectorEntry< ST > >, CCache< uint32_t >, CCache< ST >, CCache< SGSparseVectorEntry< float64_t > >, CCache< float64_t >, CCache< uint8_t >, CCache< KERNELCACHE_ELEM >, CCache< char >, CCache< uint16_t >, CCache< SGSparseVectorEntry< T > >, CMultitaskKernelMaskPairNormalizer, CSVM, CMultitaskKernelNormalizer, CNeuralNetwork, CGUIClassifier, CGaussian, CGUIFeatures, CGMM, CBinaryStream< T >, CHashedWDFeaturesTransposed, CLinearHMM, CSimpleFile< T >, CParameterCombination, CDeepBeliefNetwork, CStreamingStringFeatures< T >, CNeuralLinearLayer, CMulticlassSVM, CStateModel, CRandomKitchenSinksDotFeatures, COnlineLinearMachine, CVwParser, CPluginEstimate, CVowpalWabbit, CBinnedDotFeatures, CSVMOcas, CNeuralConvolutionalLayer, CSVRLight, CHashedWDFeatures, CPlifMatrix, CCrossValidation, CImplicitWeightedSpecFeatures, CCombinedFeatures, CSparseMatrixOperator< T >, CSNPFeatures, CWDFeatures, CKMeans, CCrossValidationMulticlassStorage, CHashedDenseFeatures< ST >, CIOBuffer, CUAIFile, CTwoStateModel, CLossFunction, CPCA, CHMSVMModel, CDeepAutoencoder, CLeastAngleRegression, CGUIKernel, CKNN, CHashedSparseFeatures< ST >, CRandomFourierGaussPreproc, CMKLMulticlass, CAutoencoder, CHypothesisTest, CExplicitSpecFeatures, CModelSelectionParameters, CLibLinearMTL, CNOCCO, CPositionalPWM, CHashedDocDotFeatures, CGUIHMM, COnlineSVMSGD, CIntegration, CJacobiEllipticFunctions, CLibLinear, CLDA, CZeroMeanCenterKernelNormalizer, CSparsePolyFeatures, CHashedMultilabelModel, CSqrtDiagKernelNormalizer, CHuberLoss, CScatterKernelNormalizer, CCplex, CFisherLDA, CHSIC, CRationalApproximation, CStochasticProximityEmbedding, CLatentModel, CMulticlassMachine, CDixonQTestRejectionStrategy, CTableFactorType, CSVMSGD, CGMNPLib, CVwCacheReader, CLBPPyrDotFeatures, CRidgeKernelNormalizer, CDependenceMaximization, CLinearMachine, CGraphCut, CMulticlassSOLabels, CSerializableAsciiFile, CSGDQN, CSNPStringKernel, CTime, CMatrixFeatures< ST >, CWeightedCommWordStringKernel, CHingeLoss, CTwoSampleTest, CSquaredLoss, CAbsoluteDeviationLoss, CExponentialLoss, CCustomKernel, CMulticlassLabels, CHash, CLinearTimeMMD, CFactor, CPlifArray, CStreamingVwFile, CQPBSVMLib, CStreamingHashedDocDotFeatures, CKernelIndependenceTest, CCustomDistance, CWeightedDegreeStringKernel, CKernelRidgeRegression, CBaggingMachine, CQDA, CNeuralLayers, CNeuralLogisticLayer, CNeuralRectifiedLinearLayer, CHierarchicalMultilabelModel, CTOPFeatures, CDiceKernelNormalizer, CMultitaskKernelMklNormalizer, CTask, CGaussianProcessClassification, CVwEnvironment, CBinaryLabels, CMultilabelModel, CMultilabelSOLabels, CDomainAdaptationSVMLinear, CCHAIDTree, CKernelTwoSampleTest, CWeightedDegreePositionStringKernel, CMAPInferImpl, CBesselKernel, CTanimotoKernelNormalizer, CCircularBuffer, CMCLDA, CGaussianDistribution, CStreamingHashedDenseFeatures< ST >, CStreamingHashedSparseFeatures< ST >, CAvgDiagKernelNormalizer, CVarianceKernelNormalizer, CMulticlassModel, COnlineLibLinear, CIndexFeatures, CCARTree, CStreamingAsciiFile, CIndependenceTest, CHierarchical, CFKFeatures, CSpectrumMismatchRBFKernel, COperatorFunction< T >, CMultilabelCLRModel, COperatorFunction< float64_t >, CCombinedKernel, CSparseSpatialSampleStringKernel, CVwRegressor, CHashedDocConverter, CFactorGraphLabels, CKLInferenceMethod, CSubsequenceStringKernel, CDotKernel, CGaussianKernel, CCommWordStringKernel, CSet< T >, CDataGenerator, CNeuralInputLayer, CSequenceLabels, CNode, CContingencyTableEvaluation, CPolyFeatures, CDenseMatrixOperator< T >, CDenseMatrixOperator< float64_t >, CChi2Kernel, CPyramidChi2, CSignal, CLibSVR, CSalzbergWordStringKernel, CStructuredLabels, CSquaredHingeLoss, CNewtonSVM, CKLApproxDiagonalInferenceMethod, CLPBoost, CVwLearner, CKLCholeskyInferenceMethod, CKLCovarianceInferenceMethod, CIterativeLinearSolver< T, ST >, CIterativeLinearSolver< float64_t, float64_t >, CIterativeLinearSolver< complex128_t, float64_t >, CIterativeLinearSolver< T, T >, CCommUlongStringKernel, CCompressor, CSVMLin, CHistogram, CGaussianShiftKernel, CGCArray< T >, CIndexBlockTree, CMultiLaplacianInferenceMethod, CNeuralSoftmaxLayer, CHomogeneousKernelMap, CLocallyLinearEmbedding, CMahalanobisDistance, CAttributeFeatures, CRandomFourierDotFeatures, CFirstElementKernelNormalizer, CMap< K, T >, CLogLoss, CLogLossMargin, CSmoothHingeLoss, CMap< TParameter *, CSGObject * >, CMap< TParameter *, SGVector< float64_t > >, CVwNativeCacheReader, CDistanceKernel, CLatentLabels, CMultilabelLabels, CKLLowerTriangularInferenceMethod, CSingleLaplacianInferenceMethodWithLBFGS, CSoftMaxLikelihood, CScatterSVM, CMMDKernelSelection, CSpectrumRBFKernel, CLogDetEstimator, CSegmentLoss, CKernelDistance, CStreamingFileFromFeatures, CLinearRidgeRegression, CGNPPLib, CPolyMatchStringKernel, CSimpleLocalityImprovedStringKernel, CKernelSelection, CDomainAdaptationSVM, CStreamingVwCacheFile, COligoStringKernel, CKLDualInferenceMethod, CEigenSolver, CCircularKernel, CConstKernel, CDiagKernel, CSphericalKernel, CLogitDVGLikelihood, CC45ClassifierTree, CMultitaskClusteredLogisticRegression, CLPM, CEmbeddingConverter, CEuclideanDistance, CWeightedMajorityVote, CMulticlassOVREvaluation, CPolyKernel, CPolyMatchWordStringKernel, CLanczosEigenSolver, CID3ClassifierTree, CMultidimensionalScaling, CStreamingFileFromDenseFeatures< T >, CStreamingFileFromSparseFeatures< T >, CStreamingFileFromStringFeatures< T >, CANOVAKernel, CProductKernel, CSparseKernel< ST >, CGaussianMatchStringKernel, CRandomForest, CKernelPCA, CNearestCentroid, CFixedDegreeStringKernel, CStringKernel< ST >, CTensorProductPairKernel, CTraceSampler, CGaussianNaiveBayes, CMulticlassOneVsRestStrategy, CStringKernel< uint16_t >, CStringKernel< char >, CStringKernel< uint64_t >, CKernelDensity, CParser, CTStudentKernel, CWaveletKernel, CGaussianProcessRegression, CDiffusionMaps, CMinkowskiMetric, CExponentialKernel, CLaplacianEigenmaps, CAttenuatedEuclideanDistance, CCauchyKernel, CLogKernel, CPowerKernel, CRationalQuadraticKernel, CDistantSegmentsKernel, CWaveKernel, CLaplacianInferenceBase, CBAHSIC, CLocalityImprovedStringKernel, CMatchWordStringKernel, CRegulatoryModulesStringKernel, CKernelMachine, CStructuredOutputMachine, CKernelDependenceMaximization, MKLMulticlassGradient, CAUCKernel, CHistogramIntersectionKernel, CSigmoidKernel, CDistanceMachine, CGaussianProcessMachine, CInverseMultiQuadricKernel, CFFDiag, CJADiag, CJADiagOrth, CLibLinearRegression, CMMDKernelSelectionCombOpt, CLocalAlignmentStringKernel, CLabelsFactory, CJediDiag, CQDiag, CUWedge, CTreeMachineNode< T >, CTreeMachineNode< ConditionalProbabilityTreeNodeData >, CTreeMachineNode< RelaxedTreeNodeData >, CTreeMachineNode< id3TreeNodeData >, CTreeMachineNode< VwConditionalProbabilityTreeNodeData >, CTreeMachineNode< CARTreeNodeData >, CTreeMachineNode< C45TreeNodeData >, CTreeMachineNode< CHAIDTreeNodeData >, CTreeMachineNode< NbodyTreeNodeData >, CMulticlassAccuracy, CGaussianARDKernel, CGaussianShortRealKernel, CMultiquadricKernel, CExactInferenceMethod, CICAConverter, CSplineKernel, CDelimiterTokenizer, CDualVariationalGaussianLikelihood, CLogitVGPiecewiseBoundLikelihood, CLogRationalApproximationIndividual, CDimensionReductionPreprocessor, CPerceptron, CHistogramWordStringKernel, CMatrixOperator< T >, CTaskTree, CMatrixOperator< float64_t >, CProbabilityDistribution, CConstMean, CStochasticGBMachine, CLinearOperator< RetType, OperandType >, CCGMShiftedFamilySolver, CIterativeShiftedLinearFamilySolver< T, ST >, CLogRationalApproximationCGM, CTreeMachine< T >, CMMDKernelSelectionCombMaxL2, CMultitaskL12LogisticRegression, CMultitaskROCEvaluation, CLinearOperator< SGVector< complex128_t >, SGVector< complex128_t > >, CLinearOperator< SGVector< T >, SGVector< T > >, CLinearOperator< SGVector< float64_t >, SGVector< float64_t > >, CIterativeShiftedLinearFamilySolver< float64_t, complex128_t >, CTreeMachine< ConditionalProbabilityTreeNodeData >, CTreeMachine< RelaxedTreeNodeData >, CTreeMachine< id3TreeNodeData >, CTreeMachine< VwConditionalProbabilityTreeNodeData >, CTreeMachine< CARTreeNodeData >, CTreeMachine< C45TreeNodeData >, CTreeMachine< CHAIDTreeNodeData >, CTreeMachine< NbodyTreeNodeData >, CCanberraMetric, CCosineDistance, CManhattanMetric, CLineReader, CJensenShannonKernel, CLinearKernel, CNumericalVGLikelihood, CLinearStructuredOutputMachine, CDualLibQPBMSOSVM, CGeodesicMetric, CJensenMetric, CTanimotoDistance, CIdentityKernelNormalizer, CLinearStringKernel, CFITCInferenceMethod, CDecompressString< ST >, CGUIConverter, CNGramTokenizer, CStudentsTVGLikelihood, CMMDKernelSelectionMedian, CChiSquareDistance, CHammingWordDistance, CLogitVGLikelihood, CProbitVGLikelihood, CRandomSearchModelSelection, CGUILabels, MKLMulticlassGLPK, CSOBI, CKernelLocallyLinearEmbedding, CSparseDistance< ST >, CCrossValidationResult, CLatentFeatures, CBinaryTreeMachineNode< T >, CMMDKernelSelectionOpt, CSparseDistance< float64_t >, CAveragedPerceptron, CFFSep, CBrayCurtisDistance, CChebyshewMetric, CFactorGraphFeatures, CRegressionLabels, CJobResultAggregator, CMulticlassOneVsOneStrategy, CNbodyTree, CSparsePreprocessor< ST >, CLeastSquaresRegression, MKLMulticlassOptimizationBase, CVwNativeCacheWriter, CJediSep, CUWedgeSep, CSparseEuclideanDistance, CRealFileFeatures, CLinearARDKernel, CSingleLaplacianInferenceMethod, CDenseMatrixExactLog, CSparseMultilabel, CGUIPluginEstimate, CVwAdaptiveLearner, CStringDistance< ST >, CStructuredAccuracy, CLinearLatentMachine, CMulticlassStrategy, CPNorm, CRescaleFeatures, CStringDistance< uint16_t >, CVwNonAdaptiveLearner, CWeightedDegreeRBFKernel, CIndependentJob, CECOCRandomSparseEncoder, CGradientCriterion, CLatentSVM, CEPInferenceMethod, CGMNPSVM, CLogPlusOne, CMixtureModel, CFactorGraphObservation, CScalarResult< T >, CDirectLinearSolverComplex, CIndividualJobResultAggregator, CNormOne, CMAPInference, CMultitaskTraceLogisticRegression, CLibSVM, CStringFileFeatures< ST >, CLinearMulticlassMachine, CRationalApproximationCGMJob, CBallTree, CKDTree, CStringPreprocessor< ST >, CStringPreprocessor< uint16_t >, CStringPreprocessor< uint64_t >, CFastICA, CCanberraWordDistance, CManhattanWordDistance, CCrossValidationOutput, CRationalApproximationIndividualJob, CECOCDiscriminantEncoder, CRandomCARTree, CSumOne, CResultSet, CTaskGroup, CGUIDistance, CStoreVectorAggregator< T >, CConjugateOrthogonalCGSolver, CSortWordString, CCCSOSVM, CIntronList, CRealNumber, CMultitaskLogisticRegression, CStoreVectorAggregator< complex128_t >, CJade, CIndexBlock, CIndexBlockGroup, CGradientModelSelection, CPruneVarSubMean, CSequence, CGUIPreprocessor, CFeatureBlockLogisticRegression, CMeanSquaredError, CMeanSquaredLogError, CLatentSOSVM, CStudentsTLikelihood, CDenseExactLogJob, CMulticlassLibLinear, CSortUlongString, CMeanAbsoluteError, CDummyFeatures, CListElement, CIsomap, CDenseDistance< ST >, CRealDistance, CIndependentComputationEngine, CVectorResult< T >, CKernelStructuredOutputMachine, CLMNN, CThresholdRejectionStrategy, CMMDKernelSelectionMax, CDenseDistance< float64_t >, CSVMLightOneClass, CLinearLocalTangentSpaceAlignment, CNeighborhoodPreservingEmbedding, CEMBase< T >, CEMMixtureModel, CClusteringAccuracy, CClusteringMutualInformation, CMultilabelAccuracy, CMeanShiftDataGenerator, CVwConditionalProbabilityTree, CEMBase< MixModelData >, CHessianLocallyLinearEmbedding, CCustomMahalanobisDistance, CCombinationRule, CStoreScalarAggregator< T >, CConjugateGradientSolver, CMMDKernelSelectionComb, CFactorGraphModel, CMultitaskLeastSquaresRegression, CLocalTangentSpaceAlignment, CSubsetStack, CGaussianLikelihood, CGridSearchModelSelection, CStochasticSOSVM, CMultitaskLinearMachine, CMajorityVote, CMeanRule, CDirectEigenSolver, CLinearSolver< T, ST >, CLinearSolver< float64_t, float64_t >, CLinearSolver< complex128_t, float64_t >, CLinearSolver< T, T >, CLocalityPreservingProjections, CGradientEvaluation, CSerialComputationEngine, CECOCEncoder, CMulticlassLibSVM, CMKLRegression, CFactorDataSource, CFactorGraph, CTaskRelation, CGaussianBlobsDataGenerator, CIndexBlockRelation, CKernelMeanMatching, CROCEvaluation, CKernelMulticlassMachine, CNormalSampler, CBalancedConditionalProbabilityTree, CFactorType, CSOSVMHelper, CDomainAdaptationMulticlassLibLinear, CMKLOneClass, CLibSVMOneClass, CMPDSVM, CGradientResult, CECOCIHDDecoder, CMulticlassTreeGuidedLogisticRegression, CConditionalProbabilityTree, CRelaxedTree, CFWSOSVM, CMKLClassification, CGPBTSVM, CSubset, CDirectSparseLinearSolver, CECOCRandomDenseEncoder, CMulticlassLogisticRegression, CMulticlassOCAS, CShareBoost, CGNPPSVM, CStratifiedCrossValidationSplitting, CPRCEvaluation, CProbitLikelihood, CSparseInverseCovariance, CCrossValidationSplitting, CDisjointSet, CDenseSubsetFeatures< ST >, CECOCForestEncoder, CGUIMath, CGUITime, CLogitLikelihood, CTDistributedStochasticNeighborEmbedding, CCrossValidationPrintOutput, CJobResult, CECOCDecoder, CFactorAnalysis, CManifoldSculpting, CCrossValidationMKLStorage, SerializableAsciiReader00, CNativeMulticlassMachine, CFunction, CECOCAEDDecoder, CECOCEDDecoder, CECOCStrategy, CData, CZeroMean, CConverter, CLOOCrossValidationSplitting, CBaseMulticlassMachine, CECOCSimpleDecoder, CECOCLLBDecoder, CStructuredData, CECOCHDDecoder, CECOCOVOEncoder, CECOCOVREncoder, CRandomConditionalProbabilityTree, and CRejectionStrategy.

virtual bool get_next_example ( )
pure virtualinherited
bool get_next_feature ( int32_t &  index,
float32_t value,
void *  iterator 
)
virtual

iterate over the non-zero features

call this function with the iterator returned by get_first_feature and call free_feature_iterator to cleanup

Parameters
indexis returned by reference (-1 when not available)
valueis returned by reference
iteratoras returned by get_first_feature
Returns
true if a new non-zero feature got returned

Definition at line 87 of file StreamingDotFeatures.cpp.

int32_t get_nnz_features_for_vector ( )
virtual

get number of non-zero features in vector

(in case accurate estimates are too expensive overestimating is OK)

Returns
number of sparse features in vector

Reimplemented in CStreamingVwFeatures, CStreamingSparseFeatures< T >, CStreamingDenseFeatures< T >, CStreamingDenseFeatures< float64_t >, and CStreamingDenseFeatures< float32_t >.

Definition at line 81 of file StreamingDotFeatures.cpp.

virtual int32_t get_num_features ( )
pure virtualinherited
int32_t get_num_preprocessed ( ) const
inherited

get the number of applied preprocs

Returns
number of applied preprocessors

Definition at line 103 of file Features.cpp.

int32_t get_num_preprocessors ( ) const
inherited

get number of preprocessors

Returns
number of preprocessors

Definition at line 155 of file Features.cpp.

virtual int32_t get_num_vectors ( ) const
pure virtualinherited
CPreprocessor * get_preprocessor ( int32_t  num) const
inherited

get specified preprocessor

Parameters
numindex of preprocessor in list

Definition at line 93 of file Features.cpp.

virtual CFeatures* get_streamed_features ( index_t  num_elements)
virtualinherited

Returns a new CFeatures instance which contains num_elements elements from the underlying stream. Not SG_REF'ed

Parameters
num_elementsnum elements to save from stream
Returns
CFeatures object of underlying type, might be smaller than requested if the stream stopped. A warning is issued in this case.

NOT IMPLEMENTED!

Reimplemented in CStreamingDenseFeatures< T >, CStreamingDenseFeatures< float64_t >, and CStreamingDenseFeatures< float32_t >.

Definition at line 191 of file StreamingFeatures.h.

CSubsetStack * get_subset_stack ( )
virtualinherited

returns subset stack

Returns
subset stack

Definition at line 334 of file Features.cpp.

bool has_property ( EFeatureProperty  p) const
inherited

check if features have given property

Parameters
pfeature property
Returns
if features have given property

Definition at line 295 of file Features.cpp.

bool is_generic ( EPrimitiveType *  generic) const
virtualinherited

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

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

Definition at line 297 of file SGObject.cpp.

bool is_preprocessed ( int32_t  num) const
inherited

get whether specified preprocessor was already applied

Parameters
numindex of preprocessor in list

Definition at line 149 of file Features.cpp.

bool is_seekable ( )
virtualinherited

Whether the stream is seekable (to check if multiple epochs are possible), i.e., whether we can process examples in a batch fashion.

A stream can usually seekable when it comes from a file or when it comes from another conventional CFeatures object.

Returns
true if seekable, else false.

Definition at line 40 of file StreamingFeatures.cpp.

void list_feature_obj ( ) const
inherited

list feature object

Definition at line 171 of file Features.cpp.

void list_preprocessors ( )
inherited

print preprocessors

Definition at line 131 of file Features.cpp.

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

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

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

Definition at line 704 of file SGObject.cpp.

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

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

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

Definition at line 545 of file SGObject.cpp.

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

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

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

Definition at line 374 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 1062 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 1057 of file SGObject.cpp.

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

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

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

Definition at line 742 of file SGObject.cpp.

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

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

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

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

Definition at line 949 of file SGObject.cpp.

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

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

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

Definition at line 889 of file SGObject.cpp.

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

Definition at line 263 of file SGObject.cpp.

void print_modsel_params ( )
inherited

prints all parameter registered for model selection and their type

Definition at line 1111 of file SGObject.cpp.

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

prints registered parameters out

Parameters
prefixprefix for members

Definition at line 309 of file SGObject.cpp.

virtual void release_example ( )
pure virtualinherited
void remove_all_subsets ( )
virtualinherited

removes all subsets Calls subset_changed_post() afterwards

Reimplemented in CCombinedFeatures.

Definition at line 328 of file Features.cpp.

void remove_subset ( )
virtualinherited

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

Reimplemented in CCombinedFeatures.

Definition at line 322 of file Features.cpp.

void reset_stream ( )
virtualinherited
bool reshape ( int32_t  num_features,
int32_t  num_vectors 
)
virtualinherited

in case there is a feature matrix allow for reshaping

NOT IMPLEMENTED!

Parameters
num_featuresnew number of features
num_vectorsnew number of vectors
Returns
if reshaping was successful

Reimplemented in CDenseFeatures< ST >, CDenseFeatures< uint32_t >, CDenseFeatures< float64_t >, CDenseFeatures< T >, and CDenseFeatures< uint16_t >.

Definition at line 165 of file Features.cpp.

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

Save this object to file.

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

Definition at line 315 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 1072 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 1067 of file SGObject.cpp.

void set_generic< complex128_t > ( )
inherited

set generic type to T

Definition at line 42 of file SGObject.cpp.

void set_global_io ( SGIO io)
inherited

set the io object

Parameters
ioio object to use

Definition at line 230 of file SGObject.cpp.

void set_global_parallel ( Parallel parallel)
inherited

set the parallel object

Parameters
parallelparallel object to use

Definition at line 243 of file SGObject.cpp.

void set_global_version ( Version version)
inherited

set the version object

Parameters
versionversion object to use

Definition at line 284 of file SGObject.cpp.

void set_preprocessed ( int32_t  num)
inherited

set applied flag for preprocessor

Parameters
numindex of preprocessor in list

Definition at line 143 of file Features.cpp.

void set_property ( EFeatureProperty  p)
inherited

set property

Parameters
pkernel property to set

Definition at line 300 of file Features.cpp.

void set_read_functions ( )
inherited

Set the vector reading functions.

The functions are implemented specific to the type in the derived class.

Definition at line 29 of file StreamingFeatures.cpp.

virtual void set_vector_and_label_reader ( )
pure virtualinherited

The derived object must set the function which will be used by the parser for reading one vector and label from the file. This function should be a member of the CStreamingFile class.

See the implementation in StreamingDenseFeatures for details.

Implemented in CStreamingHashedDocDotFeatures, CStreamingHashedDenseFeatures< ST >, CStreamingHashedSparseFeatures< ST >, CStreamingVwFeatures, CStreamingSparseFeatures< T >, CStreamingDenseFeatures< T >, CStreamingDenseFeatures< float64_t >, CStreamingDenseFeatures< float32_t >, and CStreamingStringFeatures< T >.

virtual void set_vector_reader ( )
pure virtualinherited

The derived object must set the function which will be used for reading one vector from the file. This function should be a member of the CStreamingFile class.

See the implementation in StreamingDenseFeatures for details.

Implemented in CStreamingHashedDocDotFeatures, CStreamingHashedDenseFeatures< ST >, CStreamingHashedSparseFeatures< ST >, CStreamingVwFeatures, CStreamingSparseFeatures< T >, CStreamingDenseFeatures< T >, CStreamingDenseFeatures< float64_t >, CStreamingDenseFeatures< float32_t >, and CStreamingStringFeatures< T >.

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 194 of file SGObject.cpp.

virtual void start_parser ( )
pure virtualinherited
virtual void subset_changed_post ( )
virtualinherited

method may be overwritten to update things that depend on subset

Reimplemented in CStringFeatures< ST >, CStringFeatures< T >, CStringFeatures< uint8_t >, CStringFeatures< char >, and CStringFeatures< uint16_t >.

Definition at line 293 of file Features.h.

void unset_generic ( )
inherited

unset generic type

this has to be called in classes specializing a template class

Definition at line 304 of file SGObject.cpp.

void unset_property ( EFeatureProperty  p)
inherited

unset property

Parameters
pkernel property to unset

Definition at line 305 of file Features.cpp.

void update_parameter_hash ( )
virtualinherited

Updates the hash of current parameter combination

Definition at line 250 of file SGObject.cpp.

Member Data Documentation

bool has_labels
protectedinherited

Whether examples are labelled or not.

Definition at line 201 of file StreamingFeatures.h.

SGIO* io
inherited

io

Definition at line 496 of file SGObject.h.

Parameter* m_gradient_parameters
inherited

parameters wrt which we can compute gradients

Definition at line 511 of file SGObject.h.

uint32_t m_hash
inherited

Hash of parameter values

Definition at line 517 of file SGObject.h.

Parameter* m_model_selection_parameters
inherited

model selection parameters

Definition at line 508 of file SGObject.h.

ParameterMap* m_parameter_map
inherited

map for different parameter versions

Definition at line 514 of file SGObject.h.

Parameter* m_parameters
inherited

parameters

Definition at line 505 of file SGObject.h.

CSubsetStack* m_subset_stack
protectedinherited

subset used for index transformations

Definition at line 335 of file Features.h.

Parallel* parallel
inherited

parallel

Definition at line 499 of file SGObject.h.

bool seekable
protectedinherited

Whether the stream is seekable.

Definition at line 207 of file StreamingFeatures.h.

Version* version
inherited

version

Definition at line 502 of file SGObject.h.

CStreamingFile* working_file
protectedinherited

The StreamingFile object to read from.

Definition at line 204 of file StreamingFeatures.h.


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

SHOGUN Machine Learning Toolbox - Documentation