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SHOGUN
4.1.0
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Preprocessor FisherLDA attempts to model the difference between the classes of data by performing linear discriminant analysis on input feature vectors/matrices. When the init method in FisherLDA is called with proper feature matrix X(say N number of vectors and D feature dimensions) supplied via apply_to_feature_matrix or apply_to_feature_vector methods, this creates a transformation whose outputs are the reduced T-Dimensional & class-specific distribution (where T<= number of unique classes-1). The transformation matrix is essentially a DxT matrix, the columns of which correspond to the specified number of eigenvectors which maximizes the ratio of between class matrix to within class matrix.
This class provides 3 method options to compute the transformation matrix :
CLASSIC_FLDA : This method selects W in such a way that the ratio of the between-class scatter and the within class scatter is maximized. The between class matrix is : \(\sum_b = \sum_{i=1}^C{\bf{(\mu_i-\mu)(\mu_i-\mu)^T}}\) The within class matrix is : \(\sum_w = \sum_{i=1}^C{\sum_{x_k\in}^c{\bf{(\mu_i-\mu)(\mu_i-\mu)^T}}}\) This should be choosen when N>D
CANVAR_FLDA : This method performs Canonical Variates which generalises Fisher's method to projection of more than one dimension. This is equipped to handle the cases where the within class matrix are non-invertible. Can be used for both cases(D>N or D<N). See the implementation in Bayesian Reasoning and Machine Learning by David Barber , Section 16.3
AUTO_FLDA : Automagically, the appropriate method is selected based on whether D>N (chooses CANVAR_FLDA) or D<N(chooses ::CLASSIC_FLDA)
在文件 FisherLDA.h 第 92 行定义.
Public 成员函数 | |
| CFisherLDA (EFLDAMethod method=AUTO_FLDA, float64_t thresh=0.01) | |
| virtual | ~CFisherLDA () |
| virtual bool | fit (CFeatures *features, CLabels *labels, int32_t num_dimensions=0) |
| virtual void | cleanup () |
| virtual SGMatrix< float64_t > | apply_to_feature_matrix (CFeatures *features) |
| virtual SGVector< float64_t > | apply_to_feature_vector (SGVector< float64_t > vector) |
| SGMatrix< float64_t > | get_transformation_matrix () |
| SGVector< float64_t > | get_eigenvalues () |
| SGVector< float64_t > | get_mean () |
| virtual const char * | get_name () const |
| virtual EPreprocessorType | get_type () const |
| virtual bool | init (CFeatures *data) |
| void | set_target_dim (int32_t dim) |
| int32_t | get_target_dim () const |
| void | set_distance (CDistance *distance) |
| CDistance * | get_distance () const |
| void | set_kernel (CKernel *kernel) |
| CKernel * | get_kernel () const |
| virtual CFeatures * | apply (CFeatures *features) |
| virtual EFeatureClass | get_feature_class () |
| return that we are dense features (just fixed size matrices) 更多... | |
| virtual EFeatureType | get_feature_type () |
| return feature type 更多... | |
| virtual CSGObject * | shallow_copy () const |
| virtual CSGObject * | deep_copy () const |
| virtual bool | is_generic (EPrimitiveType *generic) const |
| template<class T > | |
| void | set_generic () |
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| void | set_generic () |
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| void | set_generic () |
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| 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 () |
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| void | set_generic () |
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| 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) |
| 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 void | update_parameter_hash () |
| virtual bool | parameter_hash_changed () |
| virtual bool | equals (CSGObject *other, float64_t accuracy=0.0, bool tolerant=false) |
| virtual CSGObject * | clone () |
Public 属性 | |
| SGIO * | io |
| Parallel * | parallel |
| Version * | version |
| Parameter * | m_parameters |
| Parameter * | m_model_selection_parameters |
| Parameter * | m_gradient_parameters |
| uint32_t | m_hash |
Protected 成员函数 | |
| 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 属性 | |
| SGMatrix< float64_t > | m_transformation_matrix |
| int32_t | m_num_dim |
| float64_t | m_threshold |
| int32_t | m_method |
| SGVector< float64_t > | m_mean_vector |
| SGVector< float64_t > | m_eigenvalues_vector |
| int32_t | m_target_dim |
| CDistance * | m_distance |
| CKernel * | m_kernel |
| CEmbeddingConverter * | m_converter |
| CFisherLDA | ( | EFLDAMethod | method = AUTO_FLDA, |
| float64_t | thresh = 0.01 |
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| ) |
standard constructor
| method | LDA based on : CLASSIC_FLDA/CANVAR_FLDA/AUTO_FLDA[default] |
| thresh | threshold value for CANVAR_FLDA only. This is used to reject those basis whose singular values are less than the provided threshold. The default one is 0.01. |
在文件 FisherLDA.cpp 第 52 行定义.
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virtual |
destructor
在文件 FisherLDA.cpp 第 76 行定义.
generic interface for applying the preprocessor. used as a wrapper for apply_to_feature_matrix() method
| features | the dense input features |
实现了 CPreprocessor.
apply preprocessor to feature matrix
| features | on which the learned tranformation has to be applied. Sometimes it is also referred as projecting the given features. |
重载 CDimensionReductionPreprocessor .
在文件 FisherLDA.cpp 第 294 行定义.
apply preprocessor to feature vector
| features | on which the learned transformation has to be applied. |
重载 CDimensionReductionPreprocessor .
在文件 FisherLDA.cpp 第 331 行定义.
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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. |
在文件 SGObject.cpp 第 597 行定义.
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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.
在文件 SGObject.cpp 第 714 行定义.
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virtualinherited |
A deep copy. All the instance variables will also be copied.
在文件 SGObject.cpp 第 198 行定义.
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) |
| tolerant | allows linient check on float equality (within accuracy) |
在文件 SGObject.cpp 第 618 行定义.
fits fisher lda transformation using features and corresponding labels
| features | using which the transformation matrix will be formed |
| labels | of the given features which will be used here to find the transformation matrix unlike PCA where it is not needed. |
| dimensions | number of dimensions to retain |
在文件 FisherLDA.cpp 第 80 行定义.
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inherited |
在文件 FisherLDA.cpp 第 350 行定义.
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virtualinherited |
return that we are dense features (just fixed size matrices)
实现了 CPreprocessor.
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在文件 FisherLDA.cpp 第 355 行定义.
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在文件 SGObject.cpp 第 498 行定义.
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Returns description of a given parameter string, if it exists. SG_ERROR otherwise
| param_name | name of the parameter |
在文件 SGObject.cpp 第 522 行定义.
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Returns index of model selection parameter with provided index
| param_name | name of model selection parameter |
在文件 SGObject.cpp 第 535 行定义.
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在文件 FisherLDA.cpp 第 345 行定义.
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virtualinherited |
init set true by default, should be defined if dimension reduction preprocessor is using some initialization
实现了 CPreprocessor.
被 CPCA , 以及 CKernelPCA 重载.
在文件 DimensionReductionPreprocessor.cpp 第 58 行定义.
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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 |
在文件 SGObject.cpp 第 296 行定义.
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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 |
在文件 SGObject.cpp 第 369 行定义.
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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 occurs. |
被 CKernel, CWeightedDegreePositionStringKernel, CList, CAlphabet, CLinearHMM, CGaussianKernel, CInverseMultiQuadricKernel, CCircularKernel , 以及 CExponentialKernel 重载.
在文件 SGObject.cpp 第 426 行定义.
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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 occurs. |
被 CDynamicArray< T >, CDynamicArray< float64_t >, CDynamicArray< float32_t >, CDynamicArray< int32_t >, CDynamicArray< char >, CDynamicArray< bool > , 以及 CDynamicObjectArray 重载.
在文件 SGObject.cpp 第 421 行定义.
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virtualinherited |
在文件 SGObject.cpp 第 262 行定义.
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prints all parameter registered for model selection and their type
在文件 SGObject.cpp 第 474 行定义.
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virtualinherited |
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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 |
在文件 SGObject.cpp 第 314 行定义.
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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 occurs. |
被 CKernel 重载.
在文件 SGObject.cpp 第 436 行定义.
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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 occurs. |
被 CKernel, CDynamicArray< T >, CDynamicArray< float64_t >, CDynamicArray< float32_t >, CDynamicArray< int32_t >, CDynamicArray< char >, CDynamicArray< bool > , 以及 CDynamicObjectArray 重载.
在文件 SGObject.cpp 第 431 行定义.
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在文件 SGObject.cpp 第 41 行定义.
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inherited |
在文件 SGObject.cpp 第 46 行定义.
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inherited |
在文件 SGObject.cpp 第 51 行定义.
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inherited |
在文件 SGObject.cpp 第 56 行定义.
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inherited |
在文件 SGObject.cpp 第 61 行定义.
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inherited |
在文件 SGObject.cpp 第 66 行定义.
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inherited |
在文件 SGObject.cpp 第 71 行定义.
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inherited |
在文件 SGObject.cpp 第 76 行定义.
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inherited |
在文件 SGObject.cpp 第 81 行定义.
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inherited |
在文件 SGObject.cpp 第 86 行定义.
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inherited |
在文件 SGObject.cpp 第 91 行定义.
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inherited |
在文件 SGObject.cpp 第 96 行定义.
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inherited |
在文件 SGObject.cpp 第 101 行定义.
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inherited |
在文件 SGObject.cpp 第 106 行定义.
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inherited |
在文件 SGObject.cpp 第 111 行定义.
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inherited |
set generic type to T
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inherited |
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inherited |
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inherited |
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inherited |
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inherited |
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virtualinherited |
A shallow copy. All the SGObject instance variables will be simply assigned and SG_REF-ed.
被 CGaussianKernel 重载.
在文件 SGObject.cpp 第 192 行定义.
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inherited |
unset generic type
this has to be called in classes specializing a template class
在文件 SGObject.cpp 第 303 行定义.
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virtualinherited |
Updates the hash of current parameter combination
在文件 SGObject.cpp 第 248 行定义.
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io
在文件 SGObject.h 第 369 行定义.
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protectedinherited |
embedding converter to be used
在文件 DimensionReductionPreprocessor.h 第 127 行定义.
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protectedinherited |
distance to be used
在文件 DimensionReductionPreprocessor.h 第 121 行定义.
eigenvalues vector
在文件 FisherLDA.h 第 167 行定义.
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parameters wrt which we can compute gradients
在文件 SGObject.h 第 384 行定义.
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Hash of parameter values
在文件 SGObject.h 第 387 行定义.
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protectedinherited |
kernel to be used
在文件 DimensionReductionPreprocessor.h 第 124 行定义.
mean vector
在文件 FisherLDA.h 第 165 行定义.
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m_method
在文件 FisherLDA.h 第 163 行定义.
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model selection parameters
在文件 SGObject.h 第 381 行定义.
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num dim
在文件 FisherLDA.h 第 159 行定义.
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parameters
在文件 SGObject.h 第 378 行定义.
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protectedinherited |
target dim of dimensionality reduction preprocessor
在文件 DimensionReductionPreprocessor.h 第 118 行定义.
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m_threshold
在文件 FisherLDA.h 第 161 行定义.
transformation matrix
在文件 FisherLDA.h 第 157 行定义.
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parallel
在文件 SGObject.h 第 372 行定义.
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version
在文件 SGObject.h 第 375 行定义.
