CComparisonResults Class

# CComparisonResults Class Reference

[CADIHash.h Index] [CADIHash.h Hierarchy]

The general scheme of implementing a PicHunter like algorithm in GIFT uses the following scheme: If you want a suggestion of n<\em> elements get 2n<\em> elements More...

`#include <../libInvertedFile/include/CComparisonResults.h>`

## Public Members

- CComparisonResults (lCContainerType& inContainer, const CWeightingFunction& inPrototype, TID inID, const CRelevanceLevel& inQuery)
- double calculateImageScore (TID inDID, const CDocumentFrequencyList& inList)
- double addImageScore (TID inDID, const CDocumentFrequencyList& inList)
- CBitVector compare (const CComparisonResults& inResults)
- double getAsymmetry (const CComparisonResults& inResults)
- CWeightingFunctionPointerHash& getWeighters ()
- void setRelevanceLevel (double)
- TID getID ()
- CRelevanceLevel const& getQuery ()

## Detailed Description

The general scheme of implementing a PicHunter like algorithm in GIFT uses the following scheme:

If you want a suggestion of n<\em> elements get 2n<\em> elements. Call them the s_i.

For the same dbSize/10 (or something) elements (which we will call the e_i) calculate the distance (s_i,d_j) for all i and j possible. (Leading to something like 500 comparisons in our case).

For each s_i the delta_{ij} will be stored in a structure of the type CComparisonResults

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