K-Nearest Neighbor Graph Testing Library
C++ Python library that is able to import exisiting NN-structures; Implements Property Testing Algorithm that rejects with high probability if queries to given structure are epsilon-far from giving a K-Nearest Neighbor Graph
Public Member Functions | List of all members
KNN_Improver< V > Class Template Reference
Inheritance diagram for KNN_Improver< V >:
KNN_Tester< V >

Public Member Functions

auto improve (KNN_Graph< V > &graph, const double d, const double epsilon=0.001)
 
- Public Member Functions inherited from KNN_Tester< V >
 KNN_Tester (const bool auto_c1=true)
 
virtual Tester_Result test (const KNN_Graph< V > &graph, const double d, const double epsilon=0.001)
 
auto get_auto_c1 () const
 
void set_auto_c1 (const bool auto_c1)
 

Additional Inherited Members

- Static Public Member Functions inherited from KNN_Tester< V >
static double c1_approximate (const KNN_Graph< V > &graph)
 
- Public Attributes inherited from KNN_Tester< V >
double c1 = 1
 
double c2 = 1
 
- Protected Attributes inherited from KNN_Tester< V >
bool auto_c1
 

Member Function Documentation

template<typename V = double>
auto KNN_Improver< V >::improve ( KNN_Graph< V > &  graph,
const double  d,
const double  epsilon = 0.001 
)
inline

Property Testing Algorithm for k-Nearest Neighborhood Graphs - Graph Restauration

Parameters
KNN_GraphG, average degree of G, epsilon
Returns

The documentation for this class was generated from the following file: