Distance metrics for Nomianal Values Collection, used in K Nearest Neighbors classifier. More...
#include <KNearestNeighbor.hpp>
Collaboration diagram for faif::ml::DistanceNominalValue< Val >:
Public Types | |
| typedef Classifier< Val >::AttrValue | AttrValue |
| typedef Classifier< Val >::AttrDomain | AttrDomain |
| typedef Classifier< Val >::AttrIdd | AttrIdd |
| typedef Classifier< Val >::Domains | Domains |
| typedef Classifier< Val >::ExampleTest | ExampleTest |
Static Public Member Functions | |
| static double | distance (const ExampleTest &a, const ExampleTest &b) |
Detailed Description
template<typename Val>
class faif::ml::DistanceNominalValue< Val >
Distance metrics for Nomianal Values Collection, used in K Nearest Neighbors classifier.
distance between values is 0.0 (values equal), 0.5 (unknown value and other value) or 1.0 (different values) distance between points are sum of distances of coordinates
The documentation for this class was generated from the following file:
- faif/learning/KNearestNeighbor.hpp
