| AbstractSvmTrainer(KernelType *kernel, double C, bool offset, bool unconstrained=false) | shark::AbstractSvmTrainer< InputType, RealVector, KernelExpansion< InputType > > | inline |
| AbstractSvmTrainer(KernelType *kernel, double negativeC, double positiveC, bool offset, bool unconstrained=false) | shark::AbstractSvmTrainer< InputType, RealVector, KernelExpansion< InputType > > | inline |
| accessCount() const | shark::QpConfig | inline |
| BOOST_SERIALIZATION_SPLIT_MEMBER() | shark::ISerializable | |
| C() const | shark::AbstractSvmTrainer< InputType, RealVector, KernelExpansion< InputType > > | inline |
| cacheSize() const | shark::AbstractSvmTrainer< InputType, RealVector, KernelExpansion< InputType > > | inline |
| DatasetType typedef | shark::AbstractTrainer< Model, LabelTypeT > | |
| InputType typedef | shark::AbstractTrainer< Model, LabelTypeT > | |
| isUnconstrained() const | shark::AbstractSvmTrainer< InputType, RealVector, KernelExpansion< InputType > > | inline |
| kernel() | shark::AbstractSvmTrainer< InputType, RealVector, KernelExpansion< InputType > > | inline |
| kernel() const | shark::AbstractSvmTrainer< InputType, RealVector, KernelExpansion< InputType > > | inline |
| KernelType typedef | shark::RegularizationNetworkTrainer< InputType > | |
| LabelType typedef | shark::AbstractTrainer< Model, LabelTypeT > | |
| load(InArchive &archive, unsigned int version) | shark::ISerializable | inline |
| m_accessCount | shark::QpConfig | protected |
| m_cacheSize | shark::AbstractSvmTrainer< InputType, RealVector, KernelExpansion< InputType > > | protected |
| m_kernel | shark::AbstractSvmTrainer< InputType, RealVector, KernelExpansion< InputType > > | protected |
| m_precomputedKernelMatrix | shark::QpConfig | protected |
| m_regularizers | shark::AbstractSvmTrainer< InputType, RealVector, KernelExpansion< InputType > > | protected |
| m_s2do | shark::QpConfig | protected |
| m_shrinking | shark::QpConfig | protected |
| m_solutionproperties | shark::QpConfig | protected |
| m_sparsify | shark::QpConfig | protected |
| m_stoppingcondition | shark::QpConfig | protected |
| m_trainOffset | shark::AbstractSvmTrainer< InputType, RealVector, KernelExpansion< InputType > > | protected |
| m_unconstrained | shark::AbstractSvmTrainer< InputType, RealVector, KernelExpansion< InputType > > | protected |
| m_verbosity | shark::QpConfig | protected |
| ModelType typedef | shark::RegularizationNetworkTrainer< InputType > | |
| name() const | shark::RegularizationNetworkTrainer< InputType > | inlinevirtual |
| noiseVariance() const | shark::RegularizationNetworkTrainer< InputType > | inline |
| numberOfParameters() const | shark::AbstractSvmTrainer< InputType, RealVector, KernelExpansion< InputType > > | inlinevirtual |
| parameterVector() const | shark::AbstractSvmTrainer< InputType, RealVector, KernelExpansion< InputType > > | inlinevirtual |
| ParameterVectorType typedef | shark::IParameterizable<> | |
| precision() const | shark::RegularizationNetworkTrainer< InputType > | inline |
| precomputeKernel() | shark::QpConfig | inline |
| precomputeKernel() const | shark::QpConfig | inline |
| QpConfig(bool precomputedFlag=false, bool sparsifyFlag=true) | shark::QpConfig | inline |
| read(InArchive &archive) | shark::ISerializable | inlinevirtual |
| RegularizationNetworkTrainer(KernelType *kernel, double betaInv, bool unconstrained=false) | shark::RegularizationNetworkTrainer< InputType > | inline |
| regularizationParameters() const | shark::AbstractSvmTrainer< InputType, RealVector, KernelExpansion< InputType > > | inline |
| s2do() | shark::QpConfig | inline |
| s2do() const | shark::QpConfig | inline |
| save(OutArchive &archive, unsigned int version) const | shark::ISerializable | inline |
| setC(double C) | shark::AbstractSvmTrainer< InputType, RealVector, KernelExpansion< InputType > > | inline |
| setCacheSize(std::size_t size) | shark::AbstractSvmTrainer< InputType, RealVector, KernelExpansion< InputType > > | inline |
| setKernel(KernelType *kernel) | shark::AbstractSvmTrainer< InputType, RealVector, KernelExpansion< InputType > > | inline |
| setMaxIterations(unsigned long long i) | shark::QpConfig | inline |
| setMaxSeconds(double s) | shark::QpConfig | inline |
| setMinAccuracy(double a) | shark::QpConfig | inline |
| setNoiseVariance(double betaInv) | shark::RegularizationNetworkTrainer< InputType > | inline |
| setParameterVector(RealVector const &newParameters) | shark::AbstractSvmTrainer< InputType, RealVector, KernelExpansion< InputType > > | inlinevirtual |
| setPrecision(double beta) | shark::RegularizationNetworkTrainer< InputType > | inline |
| setRegularizationParameters(RealVector const ®ularizers) | shark::AbstractSvmTrainer< InputType, RealVector, KernelExpansion< InputType > > | inline |
| setTargetValue(double v) | shark::QpConfig | inline |
| shrinking() | shark::QpConfig | inline |
| shrinking() const | shark::QpConfig | inline |
| solutionProperties() | shark::QpConfig | inline |
| sparsify() | shark::QpConfig | inline |
| sparsify() const | shark::QpConfig | inline |
| stoppingCondition() | shark::QpConfig | inline |
| stoppingCondition() const | shark::QpConfig | inline |
| train(KernelExpansion< InputType > &svm, const LabeledData< InputType, RealVector > &dataset) | shark::RegularizationNetworkTrainer< InputType > | inline |
| AbstractSvmTrainer< InputType, RealVector, KernelExpansion< InputType > >::train(ModelType &model, DatasetType const &dataset)=0 | shark::AbstractTrainer< Model, LabelTypeT > | pure virtual |
| trainOffset() const | shark::AbstractSvmTrainer< InputType, RealVector, KernelExpansion< InputType > > | inline |
| verbosity() | shark::QpConfig | inline |
| verbosity() const | shark::QpConfig | inline |
| write(OutArchive &archive) const | shark::ISerializable | inlinevirtual |
| ~INameable() | shark::INameable | inlinevirtual |
| ~IParameterizable() | shark::IParameterizable<> | inlinevirtual |
| ~ISerializable() | shark::ISerializable | inlinevirtual |