SHOGUN  3.2.1
 All Classes Namespaces Files Functions Variables Typedefs Enumerations Enumerator Friends Macros Groups Pages
Class Hierarchy

Go to the graphical class hierarchy

This inheritance list is sorted roughly, but not completely, alphabetically:
[detail level 12345678]
oC_IterInfoStruct that contains current state of the iteration for iterative linear solvers
oCC45TreeNodeDataStructure to store data of a node of C4.5 tree. This can be used as a template type in TreeMachineNode class. Ex: C4.5 algorithm uses nodes of type CTreeMachineNode<C45TreeNodeData>
oCCARTreeNodeDataStructure to store data of a node of CART. This can be used as a template type in TreeMachineNode class. CART algorithm uses nodes of type CTreeMachineNode<CARTreeNodeData>
oCCConvolutionalFeatureMapHandles convolution and gradient calculation for a single feature map in a convolutional neural network
oCCDynInt< T, sz >Integer type of dynamic size
oCCHAIDTreeNodeDataStructure to store data of a node of CHAID. This can be used as a template type in TreeMachineNode class. CHAID algorithm uses nodes of type CTreeMachineNode<CHAIDTreeNodeData>
oCCIndirectObject< T, P >Array class that accesses elements indirectly via an index array
oCCJLCoverTreePointClass Point to use with John Langford's CoverTree. This class must have some assoficated functions defined (distance, parse_points and print, see below) so it can be used with the CoverTree implementation
oCCKNNHeapThis class implements a specialized version of max heap structure. This heap specializes in storing the least k values seen so far along with the indices (or id) of the entities with which the values are associated. On calling the push method, it is automatically checked, if the new value supplied, is among the least k distances seen so far. Also, in case the heap is full already, the max among the stored values is automatically thrown out as the new value finds its proper place in the heap
oCCLockClass Lock used for synchronization in concurrent programs
oCCLossClass which collects generic mathematical functions
oCCMatrixOperationsThe helper class is used for Laplace and KL methods
oCConditionalProbabilityTreeNodeDataStruct to store data of node of conditional probability tree
oCCSyntaxHighLightSyntax highlight
oCCTronClass Tron
oCd_node< P >
oCds_node< P >
oCDynArray< T >Template Dynamic array class that creates an array that can be used like a list or an array
oCEigenSparseUtil< T >This class contains some utilities for Eigen3 Sparse Matrix integration with shogun. Currently it provides a method for converting SGSparseMatrix to Eigen3 SparseMatrix
oCid3TreeNodeDataStructure to store data of a node of id3 tree. This can be used as a template type in TreeMachineNode class. Ex: id3 algorithm uses nodes of type CTreeMachineNode<id3TreeNodeData>
oCIndexSorter< T >
oCIterativeSolverIterator< T >Template class that is used as an iterator for an iterative linear solver. In the iteration of solving phase, each solver initializes the iteration with a maximum number of iteration limit, and relative/ absolute tolerence. They then call begin with the residual vector and continue until its end returns true, i.e. either it has converged or iteration count reached maximum limit
oCMappedSparseMatrixMapped sparse matrix for representing graph relations of tasks
oCModelClass Model
oCNbodyTreeNodeDataStructure to store data of a node of N-Body tree. This can be used as a template type in TreeMachineNode class. N-Body tree building algorithm uses nodes of type CBinaryTreeMachineNode<NbodyTreeNodeData>
oCnode< P >
oCParallelClass Parallel provides helper functions for multithreading
oCParameterParameter class
oCParameterMapImplements a map of ParameterMapElement instances Maps one key to a set of values
oCParameterMapElementClass to hold instances of a parameter map. Each element contains a key and a set of values, which each are of type SGParamInfo. May be compared to each other based on their keys
oCSGIOClass SGIO, used to do input output operations throughout shogun
oCSGParamInfoClass that holds informations about a certain parameter of an CSGObject. Contains name, type, etc. This is used for mapping types that have changed in different versions of shogun. Instances of this class may be compared to each other. Ordering is based on name, equalness is based on all attributes
oCSGReferencedDataShogun reference count managed data
|oCSGMatrix< float64_t >
|oCSGVector< complex128_t >
|oCSGVector< float64_t >
|oCSGMatrix< T >Shogun matrix
|oCSGMatrixList< T >Shogun matrix list
|oCSGNDArray< T >Shogun n-dimensional array
|oCSGSparseMatrix< T >Template class SGSparseMatrix
|oCSGSparseVector< T >Template class SGSparseVector The assumtion is that the stored SGSparseVectorEntry<T>* vector is ordered by SGSparseVectorEntry.feat_index in non-decreasing order. This has to be assured by the user of the class
|oCSGStringList< T >Template class SGStringList
|\CSGVector< T >Shogun vector
oCSGRefObjectClass SGRefObject is a reference count based memory management class
|oCCSGObjectClass SGObject is the base class of all shogun objects
|\CSGDynamicRefObjectArrayDynamic array class for CRefObject pointers that creates an array that can be used like a list or an array
oCSGSparseVectorEntry< T >Template class SGSparseVectorEntry
oCSGString< T >Shogun string
oCShogunExceptionClass ShogunException defines an exception which is thrown whenever an error inside of shogun occurs
oCSparsityStructureStruct that represents the sparsity structure of the Sparse Matrix in CRS. Implementation has been adapted from Krylstat ( Froskekongen/KRYLSTAT) library (c) Erlend Aune under GPL2+
oCsubstringStruct Substring, specified by start position and end position
oCTParameterParameter struct
oCTSGDataTypeDatatypes that shogun supports
oCv_array< T >Class v_array taken directly from JL's implementation
oCVectorDotProduct< T, Vector >Abstract template base class for vector dot product computers
oCVersionClass Version provides version information
oCVwExampleExample class for VW
oCVwFeatureOne feature in VW
\CVwLabelClass VwLabel holds a label object used by VW

SHOGUN Machine Learning Toolbox - Documentation