#include <ProximityMeasure.h>
Inheritance diagram for prapi::HistogramIntersection< T >:
The result of this measure is HI = 1sum_{i=1..N}(min(S_{i},M_{i})), where S and M represent the sample and model distributions, respectively. N is the length of the distributions.
Public Methods  
HistogramIntersection ()  
Construct a new HistogramIntersection proximity measure.  
void  setNormalized (bool normalize) 
Set the normalized state.  
bool  isNormalized (void) 
Get the normalize state.  
double  getProximity (const util::List< T > &sample, const util::List< T > &model, double stopAfter=MAXDOUBLE) const throw (ProximityException&) 
Proximity between two lists. 

Construct a new HistogramIntersection proximity measure. The measure is normalized by default. 

Proximity between two lists.
Implements prapi::ProximityMeasure< T >. 

Set the normalized state. If true, then all feature vectors given to this proximity measure are normalized prior to calculating the proximity. If false, then the feature vectors are assumed to be normalized a priori. In the latter case, the computational performance of the measure will be significantly higher. The default value is true. 