edu::tum::cs::bayesnets::learning::CPTLearner::ExampleCounter Class Reference

List of all members.

Public Member Functions

void count (int[] domainIndices, double weight)
void count (int[] domainIndices)
 ExampleCounter (CPF cpf, int[] nodeIndices)
 ExampleCounter (BeliefNode n, BeliefNetworkEx bn)

Public Attributes

int[] nodeIndices

Package Attributes

CPF cpf

Detailed Description

An instance of this class counts examples for a given node.

Definition at line 419 of file bayesnets/learning/CPTLearner.java.


Constructor & Destructor Documentation

edu::tum::cs::bayesnets::learning::CPTLearner::ExampleCounter::ExampleCounter ( BeliefNode  n,
BeliefNetworkEx  bn 
) [inline]

creates an ExampleCounter object for one of the nodes in a Bayesian network

Parameters:
n the node
bn the Bayesian Network the node is part of

Definition at line 431 of file bayesnets/learning/CPTLearner.java.

edu::tum::cs::bayesnets::learning::CPTLearner::ExampleCounter::ExampleCounter ( CPF  cpf,
int[]  nodeIndices 
) [inline]

Definition at line 444 of file bayesnets/learning/CPTLearner.java.


Member Function Documentation

void edu::tum::cs::bayesnets::learning::CPTLearner::ExampleCounter::count ( int[]  domainIndices,
double  weight 
) [inline]

adds the given weight to the value in the CPT that corresponds to the example

Parameters:
domainIndices a complete example (i.e. an example containing values for each (relevant) node) specified as an array of integers, where each value is an index into the corresponding node's domain, the order being determined by the BeliefNetwork's array of nodes as returned by getNodes().
weight the weight of the example

Definition at line 470 of file bayesnets/learning/CPTLearner.java.

void edu::tum::cs::bayesnets::learning::CPTLearner::ExampleCounter::count ( int[]  domainIndices  )  [inline]

increments the value in the CPT that corresponds to the example

Parameters:
domainIndices a complete example (i.e. an example containing values for each (relevant) node) specified as an array of integers, where each value is an index into the corresponding node's domain, the order being determined by the BeliefNetwork's array of nodes as returned by getNodes().

Definition at line 457 of file bayesnets/learning/CPTLearner.java.


Member Data Documentation

Definition at line 420 of file bayesnets/learning/CPTLearner.java.

indices of relevant nodes (parents and node itself)

Definition at line 424 of file bayesnets/learning/CPTLearner.java.


The documentation for this class was generated from the following file:
 All Classes Namespaces Files Functions Variables Enumerations


srldb
Author(s): Dominik Jain, Stefan Waldherr, Moritz Tenorth
autogenerated on Fri Jan 11 09:58:39 2013