DirectGraphicalModels::CInfer Class Reference

Base abstract class for random model inference. More...

#include <Infer.h>

Inheritance diagram for DirectGraphicalModels::CInfer:

Collaboration diagram for DirectGraphicalModels::CInfer:

Public Member Functions
	CInfer (CGraph *pGraph)
	Constructor. More...
virtual	~CInfer (void)
virtual vec_byte_t	decode (unsigned int nIt=0, Mat &lossMatrix=Mat())
	Approximate decoding. More...
virtual void	infer (unsigned int nIt=1)=0
	Inference. More...
vec_float_t	getConfidence (void) const
	Returns the confidence of the prediction. More...
vec_float_t	getPotentials (byte state) const
	Returns the potnetials for the selected state (class) More...

Additional Inherited Members
Protected Member Functions inherited from DirectGraphicalModels::CDecode
	CDecode (CGraph *pGraph)
	Constructor. More...
void	setState (vec_byte_t &state, qword configuration) const
	Sets the state according to the configuration index configuration. More...
void	incState (vec_byte_t &state) const
	Increases the state by one, i.e. switches the state array to the consequent configuration. More...
vec_float_t	calculatePotentials (void) const
	Calculates potentials for all possible configurations. More...
virtual	~CDecode (void)
virtual vec_byte_t	decode (unsigned int nIt=0, Mat &lossMatrix=Mat()) const
	Approximate decoding. More...
Static Protected Member Functions inherited from DirectGraphicalModels::CDecode
static vec_byte_t	decode (const CGraph *pGraph, Mat &lossMatrix=Mat())
	Approximate decoding. More...
static Mat	getDefaultLossMatrix (byte nStates)
	Returns a default loss matrix \(L\). More...
Protected Attributes inherited from DirectGraphicalModels::CDecode
CGraph *	m_pGraph
	Pointer to the graph. More...

Detailed Description

Base abstract class for random model inference.

Author

Sergey G. Kosov, serge.nosp@m.y.ko.nosp@m.sov@p.nosp@m.roje.nosp@m.ct-10.nosp@m..de

Definition at line 19 of file Infer.h.

Constructor & Destructor Documentation

DirectGraphicalModels::CInfer::CInfer ( CGraph *  pGraph )

inline

Constructor.

Parameters

pGraph

The graph

Definition at line 26 of file Infer.h.

virtual DirectGraphicalModels::CInfer::~CInfer ( void  )

inlinevirtual

Definition at line 27 of file Infer.h.

Member Function Documentation

virtual vec_byte_t DirectGraphicalModels::CInfer::decode ( unsigned int  nIt = 0, Mat &  lossMatrix = Mat()  )

inlinevirtual

Approximate decoding.

This function calls first inference infer() and then, using resulting marginal probabilities, estimates the most probable configuration of states (classes) in the graph via CDecode::decode().

This function modifies Node::Pot containers of graph nodes

Parameters

nIt	Number of iterations
lossMatrix	(optional) The loss matrix \(L\) (size: nStates x nStates; type: CV_32FC1). It must be a quadratic zero-diagonal matrix, whith all non-diagonal elements \(L_{i,j} > 0, \forall i\neq j\). The elemets \(L_{i,j}\) represent a loss if state \(j\) is classified as a state \(i\).

Returns

The most probable configuration

Note

This function estimates the most likely configuration, based on the marginal probabilities (potentials) in graph nodes, which in general is NOT the same as the set of most likely states, which corresponds to the configuration with the highest joint probability. In other words:

using namespace DirectGraphicalModels;
CGraph  * graph   = new CGraph(nStates);
CInfer  * inferer = new CInferExact(graph);
CDecode * decoder = new CDecodeExact(graph);
inferer->decode() == decoder->decode();       // This statement is not always true!

Definition at line 50 of file Infer.h.

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vec_float_t DirectGraphicalModels::CInfer::getConfidence

(

void

)

const

Returns the confidence of the prediction.

This function calculates the confidence values for the predicted states (classes) in the graph via CInfer::decode(). The confidence values lie in range [0; 1].

Returns

The confidence values for each node of graph.

Definition at line 6 of file Infer.cpp.

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vec_float_t DirectGraphicalModels::CInfer::getPotentials

(

byte

state

)

const

Returns the potnetials for the selected state (class)

Parameters

state

The state (class) of interest

Returns

The potential values for each node of the graph.

Definition at line 27 of file Infer.cpp.

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virtual void DirectGraphicalModels::CInfer::infer ( unsigned int  nIt = 1 )

pure virtual

Inference.

This function estimates the marginal potentials for each graph node, and stores them as node potentials

This function modifies Node::Pot containers of graph nodes

Parameters

nIt	Number of iterations

Note

This function must not to be linear, i.e. \( infer(\alpha\times N)\not\equiv\alpha\times infer(N) \)

This function substitutes the graph nodes' potentials with estimated marginal potentials

Implemented in DirectGraphicalModels::CInferExact, DirectGraphicalModels::CInferTRW, and DirectGraphicalModels::CMessagePassing.

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

• D:/Projects/DGM/modules/DGM/Infer.h
• D:/Projects/DGM/modules/DGM/Infer.cpp