public static BayesianNetworkClassifier CreateGreedyBayesianClassifier(int maxDependencies, int maxEvaluations, Dataset trainingSet, DataMining.ClassificationMeasures.IClassificationQualityMeasure qualityEvaluator, bool fireEvents)
{
CyclicRelationInvalidator invalidator = new CyclicRelationInvalidator();
invalidator.MaxDependencies = maxDependencies;
BayesianClassificationQualityEvaluator evaluator = new BayesianClassificationQualityEvaluator(qualityEvaluator);
evaluator.ValidationSet = trainingSet;
BackwardRemovalLocalSearch localSearch = new BackwardRemovalLocalSearch(evaluator);
Problem <Edge> problem = new Problem <Edge>(invalidator, null, evaluator, localSearch);
GHC hcblassifier = new GHC(0, 0, 0, problem, maxEvaluations, trainingSet, trainingSet);
if (fireEvents)
{
hcblassifier.OnPostEvaluation += new EventHandler(hcblassifier_OnPostEvaluation);
hcblassifier.OnProgress += new EventHandler(hcblassifier_OnProgress);
}
hcblassifier.Work();
BayesianNetworks.Model.BayesianNetworkClassifier bnclassifier = hcblassifier.BayesianNetworkClassifier;
return(bnclassifier);
}
public static BayesianNetworkClassifier CreateABCMinerPlusIClassifier(int seed, int iterations, int colonySize, int localColonySize, int convergence, int maxParents, Dataset trainingSet, DataMining.ClassificationMeasures.IClassificationQualityMeasure measure, bool performLocalSearch, bool fireEvents)
{
DataMining.Utilities.RandomUtility.Initialize(seed);
VariableTypeAssigmentInvalidator invalidator1 = new VariableTypeAssigmentInvalidator();
BayesianClassificationQualityEvaluator evaluator = new BayesianClassificationQualityEvaluator(measure);
SimpleVariableTypeAssignmentLocalSearch localSearch1 = new SimpleVariableTypeAssignmentLocalSearch(evaluator);
DefaultHeuristicCalculator <VariableTypeAssignment> calculator1 = new DefaultHeuristicCalculator <VariableTypeAssignment>();
Problem <VariableTypeAssignment> problem1 = new Problem <VariableTypeAssignment>(invalidator1, calculator1, evaluator, localSearch1);
CyclicRelationInvalidator invalidator2 = new CyclicRelationInvalidator();
BackwardRemovalLocalSearch localSearch2 = new BackwardRemovalLocalSearch(evaluator);
CMICalculator calculator = new CMICalculator();
Problem <Edge> problem2 = new Problem <Edge>(invalidator2, calculator, evaluator, localSearch2);
ABCMinerPlusI abcMinerPlusI = new ABCMinerPlusI(iterations, colonySize, localColonySize, convergence, problem2, problem1, maxParents, trainingSet, performLocalSearch);
if (fireEvents)
{
abcMinerPlusI.ABCAlgorithm.OnPostAntSolutionContruction += new EventHandler(abclassifier_OnPostAntSolutionContruction);
abcMinerPlusI.ABCAlgorithm.OnPostColonyIteration += new EventHandler(abclassifier_OnPostColonyIteration);
abcMinerPlusI.ABCMinerAlgorithm.OnPostAntSolutionContruction += new EventHandler(abclassifier_OnPostAntSolutionContruction);
abcMinerPlusI.ABCMinerAlgorithm.OnPostColonyIteration += new EventHandler(abclassifier_OnPostColonyIteration);
}
BayesianNetworks.Model.BayesianNetworkClassifier bnclassifier = abcMinerPlusI.CreateClassifier() as BayesianNetworkClassifier;
return(bnclassifier);
}
public static BayesianNetworkClassifier CreateABCClassifier(int seed, int iterations, int colonySize, int convergence, Dataset trainingSet, DataMining.ClassificationMeasures.IClassificationQualityMeasure measure, bool performLocalSearch, bool fireEvents)
{
DataMining.Utilities.RandomUtility.Initialize(seed);
VariableTypeAssigmentInvalidator invalidator = new VariableTypeAssigmentInvalidator();
BayesianClassificationQualityEvaluator evaluator = new BayesianClassificationQualityEvaluator(measure);
VariableTypeAssignmentLocalSearch localSearch = new VariableTypeAssignmentLocalSearch(evaluator);
DefaultHeuristicCalculator <VariableTypeAssignment> calculator = new DefaultHeuristicCalculator <VariableTypeAssignment>();
Problem <VariableTypeAssignment> problem = new Problem <VariableTypeAssignment>(invalidator, calculator, evaluator, localSearch);
ABC abc = new ABC(iterations, colonySize, convergence, problem, trainingSet, performLocalSearch);
if (fireEvents)
{
abc.OnPostAntSolutionContruction += new EventHandler(abclassifier_OnPostAntSolutionContruction);
abc.OnPostColonyIteration += new EventHandler(abclassifier_OnPostColonyIteration);
}
BayesianNetworks.Model.BayesianNetworkClassifier bnclassifier = abc.CreateClassifier() as BayesianNetworkClassifier;
return(bnclassifier);
}
public static BayesianNetworkClassifier CreateABCMinerClassifier(int seed, int iterations, int colonySize, int convergence, int dependencies, Dataset trainingSet, DataMining.ClassificationMeasures.IClassificationQualityMeasure qualityEvaluator, IHeuristicValueCalculator <Edge> calculator, bool performLocalSearch, bool fireEvents)
{
DataMining.Utilities.RandomUtility.Initialize(seed);
CyclicRelationInvalidator invalidator = new CyclicRelationInvalidator();
BayesianClassificationQualityEvaluator evaluator = new BayesianClassificationQualityEvaluator(qualityEvaluator);
BackwardRemovalLocalSearch localSearch = new BackwardRemovalLocalSearch(evaluator);
Problem <Edge> problem = new Problem <Edge>(invalidator, calculator, evaluator, localSearch);
ABCMiner abcminer = new ABCMiner(iterations, colonySize, convergence, problem, dependencies, performLocalSearch);
abcminer.Dataset = trainingSet;
if (fireEvents)
{
abcminer.OnPostAntSolutionContruction += new EventHandler(abclassifier_OnPostAntSolutionContruction);
abcminer.OnPostColonyIteration += new EventHandler(abclassifier_OnPostColonyIteration);
}
BayesianNetworks.Model.BayesianNetworkClassifier bnclassifier = abcminer.CreateClassifier() as BayesianNetworkClassifier;
return(bnclassifier);
}
