public static BayesianNetworkClassifier CreateABCMinerPlusClassifier(int seed, int iterations, int colonySize, int convergence, int maxParents, Dataset trainingSet, DataMining.ClassificationMeasures.IClassificationQualityMeasure measure, bool performLocalSearch, bool fireEvents, out BayesianNetworkClassifier abcBNClassifier)
{
DataMining.Utilities.RandomUtility.Initialize(seed);
VariableTypeAssigmentInvalidator invalidator1 = new VariableTypeAssigmentInvalidator();
BayesianClassificationQualityEvaluator evaluator = new BayesianClassificationQualityEvaluator(measure);
VariableTypeAssignmentLocalSearch localSearch1 = new VariableTypeAssignmentLocalSearch(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);
ABCMinerPlus abcMinerPlus = new ABCMinerPlus(iterations, colonySize, convergence, problem2, problem1, maxParents, trainingSet, performLocalSearch);
if (fireEvents)
{
abcMinerPlus.ABCAlgorithm.OnPostAntSolutionContruction += new EventHandler(abclassifier_OnPostAntSolutionContruction);
abcMinerPlus.ABCAlgorithm.OnPostColonyIteration += new EventHandler(abclassifier_OnPostColonyIteration);
abcMinerPlus.ABCMinerAlgorithm.OnPostAntSolutionContruction += new EventHandler(abclassifier_OnPostAntSolutionContruction);
abcMinerPlus.ABCMinerAlgorithm.OnPostColonyIteration += new EventHandler(abclassifier_OnPostColonyIteration);
abcMinerPlus.OnVariableTypeAssignmentCompleted += new EventHandler(abcMinerPlus_OnVariableTypeAssignmentCompleted);
}
BayesianNetworks.Model.BayesianNetworkClassifier bnclassifier = abcMinerPlus.CreateClassifier() as BayesianNetworkClassifier;
abcBNClassifier = abcBNClassfier;
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);
}
