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 | Static Public Member Functions | Public Attributes | Protected Attributes | List of all members
KNN_Tester< V > Class Template Reference
Inheritance diagram for KNN_Tester< V >:
KNN_Improver< V > KNN_Tester_Oracle< V >

Public Member Functions

 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)

Static Public Member Functions

static double c1_approximate (const KNN_Graph< V > &graph)

Public Attributes

double c1 = 1
double c2 = 1

Protected Attributes

bool auto_c1

Member Function Documentation

template<typename V = double>
static double KNN_Tester< V >::c1_approximate ( const KNN_Graph< V > &  graph)

Calculates approximate for c1

Numberof dimensions delta
approximate for c1
template<typename V = double>
virtual Tester_Result KNN_Tester< V >::test ( const KNN_Graph< V > &  graph,
const double  d,
const double  epsilon = 0.001 

Property Testing Algorithm for k-nearest Neighborhood Graphs

KNN_GraphG, average degree of G, epsilon
true or false

Reimplemented in KNN_Tester_Oracle< V >.

Member Data Documentation

template<typename V = double>
double KNN_Tester< V >::c1 = 1

tuning parameter c1 for psi

template<typename V = double>
double KNN_Tester< V >::c2 = 1

tuning parameter c2 for |T|

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