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latest version v1.9 - last update 24 Nov 2005 |
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#include <ltiCombination.h>
Inheritance diagram for lti::combination:
Public Member Functions | |
| combination () | |
| combination (const combination &other) | |
| virtual | ~combination () |
| virtual const char * | getTypeName () const |
| bool | apply (const std::list< classifier::outputVector > &src, classifier::outputVector &dest) const |
| bool | apply (const std::list< classifier::outputVector > &src, const dvector &weights, classifier::outputVector &dest) const |
| combination & | copy (const combination &other) |
| combination & | operator= (const combination &other) |
| virtual functor * | clone () const |
| const parameters & | getParameters () const |
Protected Member Functions | |
| bool | sumOfVectors (const std::list< classifier::outputVector > src, classifier::outputVector &dest) const |
| bool | sumOfVectors (const std::list< classifier::outputVector > src, const dvector &weights, classifier::outputVector &dest) const |
| bool | probBordaCount (const std::list< classifier::outputVector > src, classifier::outputVector &dest) const |
| bool | probBordaCount (const std::list< classifier::outputVector > src, const dvector &weights, classifier::outputVector &dest) const |
| bool | noMultAndCompatible (const std::list< classifier::outputVector > src) const |
Classes | |
| class | parameters |
| the parameters for the class combination More... | |
There are many possibilities to do this. All of them will use internaly the classifier::sortedOutput type to compute the probability for each class. You can just combine linearly the results or use the probabilistic Borda count to consider also how sure is a classifier of its result.
Probabilistic Borda Count is documented in S. Syberichs. "Entscheidungs-Fusion zur 3D-Objekterkennung in einem hierarchischen Klassifikationssystem", Diplomarbeit, Lehrstuhl für Technische Informatik, RWTH-Aachen, Juni 2001
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default constructor
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copy constructor
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destructor
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Combine the given list of classifier::outputVector objects into one outputVector object according to the parameter settings. No matter what the parameters are, the given weights will be used for combination.
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Combine the given list of classifier::outputVector objects into one outputVector object according to the parameter settings.
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returns a pointer to a clone of this functor.
Implements lti::functor. |
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copy data of "other" functor.
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returns used parameters
Reimplemented from lti::functor. |
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returns the name of this type ("combination")
Reimplemented from lti::functor. |
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Checks whether all outputVectors contained in src are compatible to each other and that none of them contains the same label more than once. Returns true if everything is ok. |
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alias for copy member
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First calculates the ProbablilisticBordaCount for each input vector then sums these measures weighted by weights and returns the sum in dest. Returns false if the vectors in src are not compatible, ie contain the same labels.
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First calculates the ProbablilisticBordaCount for each input vector then sums these measures and returns the sum in dest. Returns false if the vectors in src are not compatible, ie contain the same labels.
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Calculates the weighted sum of the outputVectors contained in src and leaves the result in dest. Returns false if the vectors in src are not compatible, ie contain the same labels.
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Calculates the sum of the outputVectors contained in src and leaves the result in dest. Returns false if the vectors in src are not compatible, ie contain the same labels.
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