| Cdismec::postproc::Sparsify::BoundData | |
| Cdismec::CacheHelper | |
| Cdismec::CascadeTrainingConfig | |
| Cdismec::confusion_matrix_detail::ConfusionMatrixBase< T > | |
| Cdismec::DataProcessing | |
| ►Cdismec::DatasetBase | |
| Cdismec::BinaryData | Collects the data related to a single optimization problem |
| Cdismec::MultiLabelData | |
| Cdismec::DismecTrainingConfig | |
| CEigen::EigenBase< Derived > | |
| Cdismec::objective::ElasticConfig | |
| Cdismec::FastSparseRowIter | This is an almost verbatim copy of the SparseFeatures::InnerIterator provided by Eigen |
| Cdismec::HashVector | An Eigen vector with versioning information, to implement simple caching of results |
| Cdismec::objective::HuberConfig | |
| Cdismec::objective::HuberPhi | |
| Cdismec::HyperParameterBase::HyperParamData< D > | This structure collects the Getter and Setter functions. This is what we store in the variant |
| ►Cdismec::HyperParameterBase | Base class for all objects that have adjustable hyper-parameters |
| Canonymous_namespace{hyperparams.cpp}::NestedTestObject | |
| Canonymous_namespace{hyperparams.cpp}::TestObject | |
| Cdismec::solvers::BacktrackingLineSearch | Backtracking line search using the armijo rule |
| Cdismec::solvers::CGMinimizer | Approximately solve a linear equation Ax + b = 0 |
| ►Cdismec::solvers::Minimizer | |
| Canonymous_namespace{minimizer.cpp}::MockMinimizer | A minimizer to be used in test cases that returns a fixed result |
| Cdismec::solvers::NewtonWithLineSearch | |
| Cdismec::solvers::NullOptimizer | Optimizer that does not change the initial vector |
| Cdismec::HyperParameters | This class represents a set of hyper-parameters |
| Cdismec::KahanAccumulator< Float > | Implements a numerically stable sum algorithm |
| Cdismec::KahanAccumulator< double > | |
| Canonymous_namespace{dense_and_sparse.cpp}::L2Regularizer | |
| Cdismec::objective::LogisticPhi | |
| Cdismec::io::LoLBinarySparse | Binary Sparse Matrix in List-of-Lists format |
| Cdismec::io::MatrixHeader | Collects the rows and columns parsed from a plain-text matrix file |
| ►Cdismec::prediction::MetricCollectionInterface | Base class for all metrics that can be calculated during the evaluation phase |
| Cdismec::prediction::ConfusionMatrixRecorder | |
| ►Cdismec::prediction::InstanceAveragedMetric | |
| Cdismec::prediction::AbandonmentAtK | |
| Cdismec::prediction::InstanceRankedPositives | |
| ►Cdismec::prediction::MetricReportInterface | |
| Cdismec::prediction::InstanceWiseMetricReporter | |
| Cdismec::prediction::MacroMetricReporter | |
| Cdismec::solvers::MinimizationResult | |
| ►Cdismec::model::Model | A model combines a set of weight with some meta-information about these weights |
| Cdismec::model::DenseModel | Implementation of the Model class that stores the weights as a single, dense matrix |
| Cdismec::model::SparseModel | |
| Cdismec::model::SubModelWrapper< T > | |
| Canonymous_namespace{numa.cpp}::NodeData | |
| Cdismec::io::NpyHeaderData | Contains the data of the header of a npy file with an array that has at most 2 dimensions |
| ►Cdismec::parallel::NUMAReplicatorBase | Base class for NUMAReplicator |
| Cdismec::parallel::NUMAReplicator< DenseRealVector > | |
| Cdismec::parallel::NUMAReplicator< const dismec::types::GenericMatrix > | |
| Cdismec::parallel::NUMAReplicator< T > | Helper class to ensure that each NUMA node has its own copy of some immutable data |
| Cdismec::opaque_int_type< Tag, T > | An integer-like type that represents categorical values |
| ►Cdismec::opaque_int_type< cpu_id_t > | |
| Cdismec::parallel::cpu_id_t | Strong typedef for an int to signify a (core of a) cpu |
| Cdismec::opaque_int_type< detail::stat_id_tag > | |
| ►Cdismec::opaque_int_type< label_id_t, std::int_fast32_t > | |
| Cdismec::label_id_t | Strong typedef for an int to signify a label id |
| ►Cdismec::opaque_int_type< numa_node_id_t > | |
| Cdismec::parallel::numa_node_id_t | Strong typedef for an int to signify a numa domain |
| ►Cdismec::opaque_int_type< thread_id_t > | |
| Cdismec::parallel::thread_id_t | Strong typedef for an int to signify a thread id |
| Cdismec::parallel::ParallelRunner | |
| ►Cdismec::io::model::PartialModelIO | This class is used as an implementation detail to capture the common code of PartialModelSaver and PartialModelLoader |
| Cdismec::io::model::PartialModelLoader | This class allows loading only a subset of the weights of a large model |
| Cdismec::io::model::PartialModelSaver | Manage saving a model consisting of multiple partial models |
| Cdismec::model::PartialModelSpec | Specifies how to interpret a weight matrix for a partial model |
| ►Cdismec::postproc::PostProcessFactory | |
| Cdismec::postproc::CombinedFactory | |
| Cdismec::postproc::GenericPostProcFactory< T, Args > | |
| Canonymous_namespace{sparse.cpp}::PredictVisitor | |
| Cdismec::PropensityModel | |
| CPyWrapper< T > | Utility class used to wrap all objects we provide to python |
| Cdismec::parallel::RunResult | |
| Cdismec::io::model::SaveOption | |
| Cdismec::stats::ScopeTimer | |
| Canonymous_namespace{sparse.cpp}::SetWeightsVisitor | |
| Cdismec::solvers::sLineSearchResult | Result of a Line Search operation |
| Cdismec::prediction::sPredLabelInfo | |
| Cdismec::objective::SquaredHingePhi | |
| Cdismec::objective::SquaredNormConfig | |
| Cdismec::TrainingStatsGatherer::StatData | |
| Cdismec::stats::StatisticMetaData | Data that is associated with each declared statistics |
| ►Cdismec::stats::Statistics | TODO maybe we should solve this with a variant which does the dispatch of expected type and tag |
| ►Cdismec::stats::StatImplBase< VectorReductionStat > | |
| Cdismec::stats::VectorReductionStat | |
| ►Cdismec::stats::StatImplBase< TaggedStat > | |
| Cdismec::stats::TaggedStat | |
| ►Cdismec::stats::StatImplBase< MultiStat > | |
| Cdismec::stats::MultiStat | |
| ►Cdismec::stats::StatImplBase< BasicStat > | |
| Cdismec::stats::BasicStat | |
| ►Cdismec::stats::StatImplBase< FullRecordStat > | |
| Cdismec::stats::FullRecordStat | |
| ►Cdismec::stats::StatImplBase< CounterStat > | |
| Cdismec::stats::CounterStat | |
| Canonymous_namespace{collection.cpp}::MockStat | |
| Cdismec::stats::StatImplBase< Derived > | Helper class for implementing Statistics classes |
| Cdismec::stats::StatisticsCollection | This class manages a collection of named Statistics objects |
| Cdismec::prediction::sTrueLabelInfo | |
| Cdismec::io::model::PartialModelLoader::SubModelRangeSpec | |
| Cdismec::stats::TagContainer | A tag container combines a name with a shared pointer, which points to the tag value |
| ►Cdismec::parallel::TaskGenerator | Base class for all parallelized operations |
| Canonymous_namespace{runner.cpp}::DummyTask | |
| Cdismec::TrainingTaskGenerator | Generates tasks for training weights for the i'th label |
| Cdismec::prediction::EvaluateMetrics | This TaskGenerator enables the calculation of evaluation metrics on top-k style sparse predictions |
| ►Cdismec::prediction::PredictionBase | Base class for handling predictions |
| Cdismec::prediction::FullPredictionTaskGenerator | |
| Cdismec::prediction::TopKPredictionTaskGenerator | |
| Cdismec::parallel::ThreadDistributor | This class helps with distributing threads to the different CPU cores |
| ►Cdismec::stats::Tracked | A base class to be used for all types that implement some for of statistics tracking |
| ►Cdismec::ResultStatsGatherer | |
| Canonymous_namespace{statistics.cpp}::DefaultGatherer | |
| ►Cdismec::init::WeightsInitializer | Base class for all weight initializers |
| Canonymous_namespace{cascade.cpp}::CombinedWeightInitializer | |
| Cdismec::init::ConstantInitializer | |
| Cdismec::init::NumpyInitializer | |
| Cdismec::init::PreTrainedInitializer | |
| ►Cdismec::init::SubsetFeatureMeanInitializer | |
| Cdismec::init::MeanOfFeaturesInitializer | |
| Cdismec::init::MultiPosMeanInitializer< Sparse > | |
| Cdismec::init::ZeroInitializer | |
| ►Cdismec::objective::Objective | Class that models an optimization objective |
| ►Cdismec::objective::PointWiseRegularizer< HuberRegularizer > | |
| Cdismec::objective::HuberRegularizer | This class implements a huber regularizer |
| ►Cdismec::objective::PointWiseRegularizer< ElasticNetRegularizer > | |
| Cdismec::objective::ElasticNetRegularizer | |
| ►Cdismec::objective::PointWiseRegularizer< SquaredNormRegularizer > | |
| Cdismec::objective::SquaredNormRegularizer | This class implements a squared norm (L2) regularizer. Thus f(x) = 0.5 |x|^2 |
| Canonymous_namespace{minimizer.cpp}::MockObjective | An objective to be used in test cases. Does not do any computations, but just resturns constants |
| ►Cdismec::objective::DenseAndSparseLinearBase | Base class for implementationa of an objective that combines dense features and sparse features |
| Cdismec::objective::DenseAndSparseMargin< MarginFunction, SparseRegFunction, DenseRegFunction > | |
| ►Cdismec::objective::LinearClassifierBase | Base class for objectives that use a linear classifier |
| ►Cdismec::objective::LinearClassifierImpBase< Regularized_SquaredHingeSVC > | |
| Cdismec::objective::Regularized_SquaredHingeSVC | |
| ►Cdismec::objective::GenericLinearClassifier | This is a non-templated, runtime-polymorphic generic implementation of the linear classifier objective |
| Cdismec::objective::GenericMarginClassifier< MarginFunction > | A utility class template that, when instatiated with a MarginFunction, produces the corresponding linear classifier loss |
| Cdismec::objective::LinearClassifierImpBase< Derived > | Implementation helper for linear classifier derived classes |
| Cdismec::objective::PointWiseRegularizer< CRTP > | Base class for pointwise regularization functions |
| ►Cdismec::postproc::PostProcessor | |
| Cdismec::postproc::CombinePostProcessor | |
| Cdismec::postproc::CullingPostProcessor | |
| Cdismec::postproc::IdentityPostProc | |
| Cdismec::postproc::ReorderPostProc | |
| Cdismec::postproc::Sparsify | |
| Cdismec::solvers::Minimizer | |
| CTrainingProgram | |
| Cdismec::TrainingResult | |
| ►Cdismec::TrainingSpec | This class gathers the setting-specific parts of the training process |
| Cdismec::CascadeTraining | |
| Cdismec::DiSMECTraining | An implementation of TrainingSpec that models the DiSMEC algorithm |
| Cdismec::TrainingStatsGatherer | |
| Cdismec::init::TypeLookup< Sparse > | |
| Cdismec::init::TypeLookup< false > | |
| Cdismec::init::TypeLookup< true > | |
| Cdismec::postproc::Sparsify::UpperBoundResult | |
| ►Cdismec::types::VarWrapBase | |
| ►Cdismec::types::EigenVariantWrapper< Eigen::Ref< Types >... > | |
| ►Cdismec::types::RefVariant< DenseRowMajor< T >, DenseColMajor< T >, SparseRowMajor< T >, SparseColMajor< T > > | |
| Cdismec::types::GenericMatrixRef< T > | |
| ►Cdismec::types::RefVariant< DenseVector< T >, SparseVector< T > > | |
| Cdismec::types::GenericVectorRef< T > | |
| Cdismec::types::RefVariant< Types > | |
| ►Cdismec::types::EigenVariantWrapper< Dense, Sparse > | |
| Cdismec::types::GenericMatrix< Dense, Sparse > | |
| Cdismec::types::EigenVariantWrapper< Types > | |
| Cdismec::VectorHash | A unique identifier for a HashVector |
| Canonymous_namespace{transform.cpp}::VisitorBias | |
| Cdismec::io::model::WeightFileEntry | Collect the data about a weight file |
| ►Cdismec::WeightingScheme | Base class for label-based weighting schemes |
| Cdismec::ConstantWeighting | Simple weighting scheme that assigns the same weighting to all label_ids |
| Cdismec::CustomWeighting | |
| Cdismec::PropensityDownWeighting | |
| Cdismec::PropensityWeighting | |
| ►Cdismec::init::WeightInitializationStrategy | Base class for all weight init strategies |
| Cdismec::init::ConstantInitializationStrategy | An initialization strategy that sets the weight vector to a given constant |
| Cdismec::init::NumpyInitializationStrategy | |
| Cdismec::init::PreTrainedInitializationStrategy | |
| ►Cdismec::init::SubsetFeatureMeanStrategy | |
| Cdismec::init::MeanOfFeaturesStrategy | |
| Cdismec::init::MultiPosMeanStrategy | |
| Cdismec::init::ZeroInitializationStrategy | |
| Canonymous_namespace{xmc.cpp}::XMCHeader | Collects the data from the header of an xmc file XMC data format |
| Canonymous_namespace{dense_and_sparse.cpp}::ZeroPhi | |
1.9.1