 arpack_wrapper< Scalar, RealScalar > | |
 arpack_wrapper< double, double > | |
 arpack_wrapper< float, float > | |
 ArpackGeneralizedSelfAdjointEigenSolver< LMatrixType, RMatrixType, MatrixOperation, BisSPD > | |
 BatchCallbackTraits< Callback > | |
 CallbacksInitializedState< KernelCallback, DistanceCallback, FeaturesCallback > | |
 Cell | |
 CheckedParameter | |
 CheckerPolicyBase | |
  PointerCheckerPolicyImpl< T > | |
  PointerCheckerPolicyImpl< double > | |
  PointerCheckerPolicyImpl< float > | |
  PointerCheckerPolicyImpl< int > | |
 compare_impl< Type, RandomAccessIterator, DistanceCallback > | |
 compare_impl< DistanceType, RandomAccessIterator, DistanceCallback > | |
 compare_impl< KernelType, RandomAccessIterator, DistanceCallback > | |
 conditional_select< bool, T > | |
 conditional_select< false, T > | |
 conditional_select< true, T > | |
 Context | |
 CoverTreePoint< 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 |
 d_node< P > | |
 DataForErrorFunc | Data needed to compute error function |
 DataPoint | |
 DefaultValue | |
 DenseImplicitSquareMatrixOperation | Matrix-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 |
 DenseImplicitSquareSymmetricMatrixOperation | Matrix-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 |
 DenseInverseMatrixOperation | Matrix-matrix operation used to compute smallest eigenvalues and associated eigenvectors of a dense matrix Essentially solves linear system with provided right-hand side part |
 DenseMatrixOperation | Matrix-matrix operation used to compute largest eigenvalues and associated eigenvectors. Essentially computes matrix product with provided right-hand side part |
 distance_impl< Type, RandomAccessIterator, Callback > | |
 distance_impl< DistanceType, RandomAccessIterator, Callback > | |
 distance_impl< KernelType, RandomAccessIterator, Callback > | |
 DistanceAndFeaturesInitializedState< DistanceCallback, FeaturesCallback > | |
 VpTree< T, distance >::DistanceComparator | |
 DistanceComparator< RandomAccessIterator, DistanceCallback > | |
 DistanceFirstInitializedState< DistanceCallback > | |
 distances_comparator< DistanceRecord > | |
 DistanceType | |
 ds_node< P > | |
 dummy_distance_callback< Data > | |
 dummy_features_callback< Data > | |
 dummy_kernel_callback< Data > | |
 eigen_distance_callback | |
 eigen_features_callback | |
 eigen_kernel_callback | |
 EmptyType | |
 exception | STL class |
  logic_error | STL class |
   missed_parameter_error | An exception type that is thrown in case of missed parameter, i.e. when some required parameter is not set |
   unsupported_method_error | An exception type that is thrown when unsupported method is called |
   wrong_parameter_error | An exception type that is thrown in case if wrong parameter value is passed |
   wrong_parameter_type_error | An exception type that is thrown in case if wrong parameter value is passed |
  runtime_error | STL class |
   eigendecomposition_error | An exception type that is thrown when eigendecomposition is failed |
   multiple_parameter_error | An exception type that is thrown when some parameter is passed more than once |
   not_enough_memory_error | An exception type that is thrown when the library can't get enough memory |
  cancelled_exception | An exception type that is thrown when computations were cancelled |
 FeaturesFirstInitializedState< FeaturesCallback > | |
 fibonacci_heap | Class fibonacci_heap, a fibonacci heap. Generally used by Isomap for Dijkstra heap algorithm |
 fibonacci_heap_node | |
 VpTree< T, distance >::HeapItem | |
 VantagePointTree< RandomAccessIterator, DistanceCallback >::HeapItem | |
 ImplementationBase< RandomAccessIterator, KernelCallback, DistanceCallback, FeaturesCallback > | |
 initialize | |
 is_dummy< T > | |
 KernelAndDistanceInitializedState< KernelCallback, DistanceCallback > | |
 KernelAndFeaturesInitializedState< KernelCallback, FeaturesCallback > | |
 KernelDistance< RandomAccessIterator, Callback > | |
 KernelDistance< RandomAccessIterator, KernelCallback > | |
 KernelFirstInitializedState< KernelCallback > | |
 KernelType | |
 LoggerImplementation | A base class for logger required by the library |
  DefaultLoggerImplementation | Default std::cout implementation of LoggerImplementation |
 LoggingSingleton | Main logging singleton used by the library. Can use provided LoggerImplementation if necessary. By default uses DefaultLoggerImplementation |
 Message | |
 MethodTraits< method > | Traits used to obtain information about dimension reduction methods compile-time |
 neighbors_finder< RandomAccessIterator > | |
 VpTree< T, distance >::Node | |
 VantagePointTree< RandomAccessIterator, DistanceCallback >::Node | |
 node< P > | |
 Parameter | |
 ParameterKeyword< T > | |
 ParametersInitializedState | |
 ParametersSet | |
 pimpl_distance_callback< Implementation > | |
 pimpl_kernel_callback< Implementation > | |
 PlainDistance< RandomAccessIterator, Callback > | |
 PlainDistance< RandomAccessIterator, DistanceCallback > | |
 precomputed_distance_callback | |
 precomputed_kernel_callback | |
 priority_queue< T > | STL class |
  reservable_priority_queue< T, Comparator > | |
 ProjectingFunction | A pimpl wrapper for projecting function |
 ProjectionImplementation | A base class for implementation of projecting |
  MatrixProjectionImplementation | Basic ProjectionImplementation that subtracts mean from the vector and multiplies projecting matrix with it |
 QuadTree | |
 SparseInverseMatrixOperation | Matrix-matrix operation used to compute smallest eigenvalues and associated eigenvectors of a sparse matrix Essentially solves linear system with provided right-hand side part |
 TapkeeOutput | Return result of the library - a pair of DenseMatrix (embedding) and ProjectingFunction |
 timed_context | |
 TSNE | |
 TypePolicyBase | |
  PointerTypePolicyImpl< T > | |
 v_array< T > | Class v_array taken directly from JL's implementation |
 v_array< ScalarType > | |
 ValueKeeper | |
 VantagePointTree< RandomAccessIterator, DistanceCallback > | |
 VpTree< T, distance > | |