Tapkee
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Class Hierarchy
This inheritance list is sorted roughly, but not completely, alphabetically:
[detail level 123]
oCany_wrapper
oCarpack_wrapper< Scalar, RealScalar >
oCarpack_wrapper< double, double >
oCarpack_wrapper< float, float >
oCArpackGeneralizedSelfAdjointEigenSolver< LMatrixType, RMatrixType, MatrixOperation, BisSPD >
oCBatchCallbackTraits< Callback >
oCCallbacksInitializedState< KernelCallback, DistanceCallback, FeaturesCallback >
oCCell
oCCheckedParameter
oCcompare_impl< Type, RandomAccessIterator, DistanceCallback >
oCcompare_impl< DistanceType, RandomAccessIterator, DistanceCallback >
oCcompare_impl< KernelType, RandomAccessIterator, DistanceCallback >
oCcompile_time_assert< bool >
oCcompile_time_assert< std::numeric_limits< T >::is_integer >
oCcompile_time_assert< std::numeric_limits< T >::is_specialized >
oCcompile_time_assert< true >
oCconditional_select< bool, T >
oCconditional_select< false, T >
oCconditional_select< true, T >
oCContext
oCCoverTreePoint< RandomAccessIterator >Class Point to use with John Langford's CoverTree. This class must have some associated functions defined (distance, and print, see below) so it can be used with the CoverTree implementation
oCd_node< P >
oCDataForErrorFuncData needed to compute error function
oCDataPoint
oCDefaultValue
oCDenseImplicitSquareMatrixOperationMatrix-matrix operation used to compute largest eigenvalues and associated eigenvectors of X*X^T like matrix implicitly. Essentially computes matrix product with provided right-hand side part twice
oCDenseImplicitSquareSymmetricMatrixOperationMatrix-matrix operation used to compute largest eigenvalues and associated eigenvectors of X*X^T like matrix implicitly. Essentially computes matrix product with provided right-hand side part twice
oCDenseInverseMatrixOperationMatrix-matrix operation used to compute smallest eigenvalues and associated eigenvectors of a dense matrix Essentially solves linear system with provided right-hand side part
oCDenseMatrixOperationMatrix-matrix operation used to compute largest eigenvalues and associated eigenvectors. Essentially computes matrix product with provided right-hand side part
oCdistance_impl< Type, RandomAccessIterator, Callback >
oCdistance_impl< DistanceType, RandomAccessIterator, Callback >
oCdistance_impl< KernelType, RandomAccessIterator, Callback >
oCDistanceAndFeaturesInitializedState< DistanceCallback, FeaturesCallback >
oCVpTree< T, distance >::DistanceComparator
oCDistanceComparator< RandomAccessIterator, DistanceCallback >
oCDistanceFirstInitializedState< DistanceCallback >
oCdistances_comparator< DistanceRecord >
oCDistanceType
oCds_node< P >
oCdummy_distance_callback< Data >
oCdummy_features_callback< Data >
oCdummy_kernel_callback< Data >
oCeigen_distance_callback
oCeigen_features_callback
oCeigen_kernel_callback
oCeigendecomposition_impl< MatrixType >
oCeigendecomposition_impl< DenseMatrix >
oCeigendecomposition_impl< SparseWeightMatrix >
oCEmptyType
oCexceptionSTL class
oCFeaturesFirstInitializedState< FeaturesCallback >
oCfibonacci_heapClass fibonacci_heap, a fibonacci heap. Generally used by Isomap for Dijkstra heap algorithm
oCfibonacci_heap_node
oCgeneralized_eigendecomposition_impl< LMatrixType, RMatrixType >
oCgeneralized_eigendecomposition_impl< DenseMatrix, DenseMatrix >
oCgeneralized_eigendecomposition_impl< SparseWeightMatrix, DenseDiagonalMatrix >
oCVpTree< T, distance >::HeapItem
oCVantagePointTree< RandomAccessIterator, DistanceCallback >::HeapItem
oCHexWrapper< T >
oCImplementationBase< RandomAccessIterator, KernelCallback, DistanceCallback, FeaturesCallback >
oCInClosedRange< T >
oCinitialize
oCInRange< T >
oCis_dummy< T >
oCKernelAndDistanceInitializedState< KernelCallback, DistanceCallback >
oCKernelAndFeaturesInitializedState< KernelCallback, FeaturesCallback >
oCKernelDistance< RandomAccessIterator, Callback >
oCKernelDistance< RandomAccessIterator, KernelCallback >
oCKernelFirstInitializedState< KernelCallback >
oCKernelType
oCLoggerImplementationA base class for logger required by the library
oCLoggingSingletonMain logging singleton used by the library. Can use provided LoggerImplementation if necessary. By default uses DefaultLoggerImplementation
oCMethod< M >
oCMethod< ComputationStrategy >
oCMethod< EigendecompositionStrategy >
oCMethod< EigenMethod >
oCMethod< NeighborsMethod >
oCMethodTraits< method >Traits used to obtain information about dimension reduction methods compile-time
oCneighbors_finder< RandomAccessIterator >
oCVpTree< T, distance >::Node
oCnode< P >
oCVantagePointTree< RandomAccessIterator, DistanceCallback >::Node
oCNonNegativity< T >
oCOctWrapper< T >
oCParameter
oCParameterKeyword< T >
oCParametersForwarder
oCParametersInitializedState
oCParametersSet
oCpimpl_distance_callback< Implementation >
oCpimpl_kernel_callback< Implementation >
oCPlainDistance< RandomAccessIterator, Callback >
oCPlainDistance< RandomAccessIterator, DistanceCallback >
oCPositivity< T >
oCPrecisionWrapper< T >
oCPrecisionWrapperBuilder
oCPrecisionWrapperBuilderHelper
oCprecomputed_distance_callback
oCprecomputed_kernel_callback
oCpriority_queue< T >STL class
oCProjectingFunctionA pimpl wrapper for projecting function
oCProjectionImplementationA base class for implementation of projecting
oCQuadTree
oCrepr_impl_if_streaming_supported< T, bool >
oCrepr_impl_if_streaming_supported< T, false >
oCrepr_impl_if_streaming_supported< T, true >
oCSparseInverseMatrixOperationMatrix-matrix operation used to compute smallest eigenvalues and associated eigenvectors of a sparse matrix Essentially solves linear system with provided right-hand side part
oCsupports_saving< S, T >
oCTapkeeOutputReturn result of the library - a pair of DenseMatrix (embedding) and ProjectingFunction
oCtimed_context
oCTSNE
oCTypePolicyBase
oCv_array< T >Class v_array taken directly from JL's implementation
oCv_array< ScalarType >
oCValueKeeper
oCValueWrapper
oCValueWrapperImplementationBase
oCVantagePointTree< RandomAccessIterator, DistanceCallback >
oCVpTree< T, distance >
oCWidthWrapper< T >
oCWidthWrapperBuilder
\CWidthWrapperBuilderHelper