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SHOGUN
v1.1.0
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SHOGUN
v1.1.0
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Class KRR implements Kernel Ridge Regression - a regularized least square method for classification and regression.
It is similar to support vector machines (cf. CSVM). However in contrast to SVMs a different objective is optimized that leads to a dense solution (thus not only a few support vectors are active in the end but all training examples). This makes it only applicable to rather few (a couple of thousand) training examples. In case a linear kernel is used RR is closely related to Fishers Linear Discriminant (cf. LDA).
Internally (for linear kernels) it is solved via minimizing the following system
![\[ \frac{1}{2}\left(\sum_{i=1}^N(y_i-{\bf w}\cdot {\bf x}_i)^2 + \tau||{\bf w}||^2\right) \]](form_202.png)
which is boils down to solving a linear system
![\[ {\bf w} = \left(\tau {\bf I}+ \sum_{i=1}^N{\bf x}_i{\bf x}_i^T\right)^{-1}\left(\sum_{i=1}^N y_i{\bf x}_i\right) \]](form_203.png)
and in the kernel case
![\[ {\bf \alpha}=\left({\bf K}+\tau{\bf I}\right)^{-1}{\bf y} \]](form_204.png)
where K is the kernel matrix and y the vector of labels. The expressed solution can again be written as a linear combination of kernels (cf. CKernelMachine) with bias 
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Public Member Functions | |
| CKRR () | |
| CKRR (float64_t tau, CKernel *k, CLabels *lab) | |
| virtual | ~CKRR () |
| void | set_tau (float64_t t) |
| virtual CLabels * | apply () |
| virtual float64_t | apply (int32_t num) |
| virtual bool | load (FILE *srcfile) |
| virtual bool | save (FILE *dstfile) |
| virtual EClassifierType | get_classifier_type () |
| virtual const char * | get_name () const |
 Public Member Functions inherited from CKernelMachine | |
| CKernelMachine () | |
| virtual | ~CKernelMachine () |
| void | set_kernel (CKernel *k) |
| CKernel * | get_kernel () |
| void | set_batch_computation_enabled (bool enable) |
| bool | get_batch_computation_enabled () |
| void | set_linadd_enabled (bool enable) |
| bool | get_linadd_enabled () |
| void | set_bias_enabled (bool enable_bias) |
| bool | get_bias_enabled () |
| float64_t | get_bias () |
| void | set_bias (float64_t bias) |
| int32_t | get_support_vector (int32_t idx) |
| float64_t | get_alpha (int32_t idx) |
| bool | set_support_vector (int32_t idx, int32_t val) |
| bool | set_alpha (int32_t idx, float64_t val) |
| int32_t | get_num_support_vectors () |
| void | set_alphas (SGVector< float64_t > alphas) |
| void | set_support_vectors (SGVector< int32_t > svs) |
| SGVector< int32_t > | get_support_vectors () |
| SGVector< float64_t > | get_alphas () |
| bool | create_new_model (int32_t num) |
| bool | init_kernel_optimization () |
| virtual CLabels * | apply (CFeatures *data) |
| Public Member Functions inherited from CMachine | |
| CMachine () | |
| virtual | ~CMachine () |
| virtual bool | train (CFeatures *data=NULL) |
| virtual void | set_labels (CLabels *lab) |
| virtual CLabels * | get_labels () |
| virtual float64_t | get_label (int32_t i) |
| void | set_max_train_time (float64_t t) |
| float64_t | get_max_train_time () |
| void | set_solver_type (ESolverType st) |
| ESolverType | get_solver_type () |
| virtual void | set_store_model_features (bool store_model) |
| Public Member Functions inherited from CSGObject | |
| CSGObject () | |
| CSGObject (const CSGObject &orig) | |
| virtual | ~CSGObject () |
| 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="") |
| 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 () |
| SGVector< char * > | get_modelsel_names () |
| char * | get_modsel_param_descr (const char *param_name) |
| index_t | get_modsel_param_index (const char *param_name) |
Protected Member Functions | |
| virtual bool | train_machine (CFeatures *data=NULL) |
| Protected Member Functions inherited from CKernelMachine | |
| virtual void | store_model_features () |
Additional Inherited Members | |
| Static Public Member Functions inherited from CKernelMachine | |
| static void * | apply_helper (void *p) |
| Public Attributes inherited from CSGObject | |
| SGIO * | io |
| Parallel * | parallel |
| Version * | version |
| Parameter * | m_parameters |
| Parameter * | m_model_selection_parameters |
| Protected Attributes inherited from CKernelMachine | |
| CKernel * | kernel |
| bool | use_batch_computation |
| bool | use_linadd |
| bool | use_bias |
| float64_t | m_bias |
| SGVector< float64_t > | m_alpha |
| SGVector< int32_t > | m_svs |
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classify one example
| num | which example to classify |
Reimplemented from CKernelMachine.
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| void set_tau | ( | float64_t | t | ) |
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