Super class of all support vector machine trainers. More...
#include <shark/Algorithms/Trainers/AbstractSvmTrainer.h>
Public Member Functions | |
QpConfig (bool precomputedFlag=false, bool sparsifyFlag=true) | |
Constructor. More... | |
QpStoppingCondition & | stoppingCondition () |
Read/write access to the stopping condition. More... | |
QpStoppingCondition const & | stoppingCondition () const |
Read access to the stopping condition. More... | |
QpSolutionProperties & | solutionProperties () |
Access to the solution properties. More... | |
bool & | precomputeKernel () |
Flag for using a precomputed kernel matrix. More... | |
bool const & | precomputeKernel () const |
Flag for using a precomputed kernel matrix. More... | |
bool & | sparsify () |
Flag for sparsifying the model after training. More... | |
bool const & | sparsify () const |
Flag for sparsifying the model after training. More... | |
bool & | shrinking () |
Flag for shrinking in the decomposition solver. More... | |
bool const & | shrinking () const |
Flag for shrinking in the decomposition solver. More... | |
bool & | s2do () |
Flag for S2DO (instead of SMO) More... | |
bool const & | s2do () const |
Flag for S2DO (instead of SMO) More... | |
unsigned int & | verbosity () |
Verbosity level of the solver. More... | |
unsigned int const & | verbosity () const |
Verbosity level of the solver. More... | |
unsigned long long const & | accessCount () const |
Number of kernel accesses. More... | |
void | setMinAccuracy (double a) |
void | setMaxIterations (unsigned long long i) |
void | setTargetValue (double v) |
void | setMaxSeconds (double s) |
Protected Attributes | |
QpStoppingCondition | m_stoppingcondition |
conditions for when to stop the QP solver More... | |
QpSolutionProperties | m_solutionproperties |
properties of the approximate solution found by the solver More... | |
bool | m_precomputedKernelMatrix |
should the solver use a precomputed kernel matrix? More... | |
bool | m_sparsify |
should the trainer sparsify the model after training? More... | |
bool | m_shrinking |
should shrinking be used? More... | |
bool | m_s2do |
should S2DO be used instead of SMO? More... | |
unsigned int | m_verbosity |
verbosity level (currently unused) More... | |
unsigned long long | m_accessCount |
kernel access count More... | |
Super class of all support vector machine trainers.
Definition at line 71 of file AbstractSvmTrainer.h.
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Constructor.
Definition at line 75 of file AbstractSvmTrainer.h.
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Number of kernel accesses.
Definition at line 137 of file AbstractSvmTrainer.h.
References m_accessCount.
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Flag for using a precomputed kernel matrix.
Definition at line 97 of file AbstractSvmTrainer.h.
References m_precomputedKernelMatrix.
Referenced by shark::CSvmTrainer< InputType, CacheType >::get_db_dParams(), shark::EpsilonSvmTrainer< InputType, CacheType >::train(), shark::OneClassSvmTrainer< InputType, CacheType >::train(), shark::RankingSvmTrainer< InputType, CacheType >::train(), and shark::SquaredHingeCSvmTrainer< InputType, CacheType >::train().
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Flag for using a precomputed kernel matrix.
Definition at line 101 of file AbstractSvmTrainer.h.
References m_precomputedKernelMatrix.
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Flag for S2DO (instead of SMO)
Definition at line 121 of file AbstractSvmTrainer.h.
References m_s2do.
Referenced by shark::CSvmTrainer< InputType, CacheType >::get_db_dParams().
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Flag for S2DO (instead of SMO)
Definition at line 125 of file AbstractSvmTrainer.h.
References m_s2do.
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Definition at line 143 of file AbstractSvmTrainer.h.
References m_stoppingcondition, and shark::QpStoppingCondition::maxIterations.
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Definition at line 147 of file AbstractSvmTrainer.h.
References m_stoppingcondition, and shark::QpStoppingCondition::maxSeconds.
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Definition at line 141 of file AbstractSvmTrainer.h.
References m_stoppingcondition, and shark::QpStoppingCondition::minAccuracy.
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Definition at line 145 of file AbstractSvmTrainer.h.
References m_stoppingcondition, and shark::QpStoppingCondition::targetValue.
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Flag for shrinking in the decomposition solver.
Definition at line 113 of file AbstractSvmTrainer.h.
References m_shrinking.
Referenced by shark::CSvmTrainer< InputType, CacheType >::get_db_dParams().
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Flag for shrinking in the decomposition solver.
Definition at line 117 of file AbstractSvmTrainer.h.
References m_shrinking.
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Access to the solution properties.
Definition at line 93 of file AbstractSvmTrainer.h.
References m_solutionproperties.
Referenced by shark::CSvmTrainer< InputType, CacheType >::get_db_dParams(), main(), shark::MissingFeatureSvmTrainer< InputType, CacheType >::setMaxIterations(), shark::EpsilonSvmTrainer< InputType, CacheType >::train(), shark::RankingSvmTrainer< InputType, CacheType >::train(), shark::LinearCSvmTrainer< InputType >::train(), and shark::SquaredHingeLinearCSvmTrainer< InputType >::train().
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Flag for sparsifying the model after training.
Definition at line 105 of file AbstractSvmTrainer.h.
References m_sparsify.
Referenced by shark::CSvmTrainer< InputType, CacheType >::get_db_dParams(), main(), shark::EpsilonSvmTrainer< InputType, CacheType >::train(), and shark::OneClassSvmTrainer< InputType, CacheType >::train().
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Flag for sparsifying the model after training.
Definition at line 109 of file AbstractSvmTrainer.h.
References m_sparsify.
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Read/write access to the stopping condition.
Definition at line 85 of file AbstractSvmTrainer.h.
References m_stoppingcondition.
Referenced by shark::CSvmTrainer< InputType, CacheType >::get_db_dParams(), main(), shark::MissingFeatureSvmTrainer< InputType, CacheType >::setMaxIterations(), shark::EpsilonSvmTrainer< InputType, CacheType >::train(), shark::RankingSvmTrainer< InputType, CacheType >::train(), shark::LinearCSvmTrainer< InputType >::train(), and shark::SquaredHingeLinearCSvmTrainer< InputType >::train().
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Read access to the stopping condition.
Definition at line 89 of file AbstractSvmTrainer.h.
References m_stoppingcondition.
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Verbosity level of the solver.
Definition at line 129 of file AbstractSvmTrainer.h.
References m_verbosity.
Referenced by shark::CSvmTrainer< InputType, CacheType >::get_db_dParams(), shark::LinearCSvmTrainer< InputType >::train(), and shark::SquaredHingeLinearCSvmTrainer< InputType >::train().
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Verbosity level of the solver.
Definition at line 133 of file AbstractSvmTrainer.h.
References m_verbosity.
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kernel access count
Definition at line 165 of file AbstractSvmTrainer.h.
Referenced by accessCount().
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should the solver use a precomputed kernel matrix?
Definition at line 155 of file AbstractSvmTrainer.h.
Referenced by precomputeKernel().
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should S2DO be used instead of SMO?
Definition at line 161 of file AbstractSvmTrainer.h.
Referenced by s2do().
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should shrinking be used?
Definition at line 159 of file AbstractSvmTrainer.h.
Referenced by shark::MissingFeatureSvmTrainer< InputType, CacheType >::setMaxIterations(), shrinking(), shark::EpsilonSvmTrainer< InputType, CacheType >::train(), and shark::RankingSvmTrainer< InputType, CacheType >::train().
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properties of the approximate solution found by the solver
Definition at line 153 of file AbstractSvmTrainer.h.
Referenced by shark::AbstractLinearSvmTrainer< InputType >::numberOfParameters(), and solutionProperties().
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should the trainer sparsify the model after training?
Definition at line 157 of file AbstractSvmTrainer.h.
Referenced by sparsify().
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conditions for when to stop the QP solver
Definition at line 151 of file AbstractSvmTrainer.h.
Referenced by shark::AbstractLinearSvmTrainer< InputType >::numberOfParameters(), setMaxIterations(), setMaxSeconds(), setMinAccuracy(), setTargetValue(), and stoppingCondition().
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verbosity level (currently unused)
Definition at line 163 of file AbstractSvmTrainer.h.
Referenced by shark::AbstractLinearSvmTrainer< InputType >::numberOfParameters(), and verbosity().