public iFourmi.DataMining.Model.IClassifier CreateClassifier()
{
Solution <Edge> solution = new Solution <Edge>();
CyclicRelationInvalidator invalidator = new CyclicRelationInvalidator();
invalidator.MaxDependencies = 1;
ConstructionGraph <Edge> constructionGraph = ConstructionGraphBuilder.BuildBNConstructionGraph(this._trainingset.Metadata);
CMICalculator cmiCalculator = new CMICalculator();
cmiCalculator.Dataset = this._trainingset;
constructionGraph.SetHeuristicValues(cmiCalculator, false);
List <DecisionComponent <Edge> > components = constructionGraph.Components.OrderByDescending(e => e.Heuristic).ToList();
while (components.Count != 0)
{
DecisionComponent <Edge> component = components[0];
solution.Components.Add(component);
invalidator.Invalidate(component, solution, constructionGraph);
components = constructionGraph.Components.Where(e => e.IsValid).OrderByDescending(e => e.Heuristic).ToList();
}
BayesianNetworkClassifier BNClassifier = new BayesianNetworks.Model.BayesianNetworkClassifier(this._trainingset.Metadata, solution.ToList());
BNClassifier.LearnParameters(this._trainingset);
return(BNClassifier);
}
public ACOB(int maxIterations, int colonySize, int convergenceIterations, Problem <Edge> problem, int maxDependencies, Dataset trainingset)
: base(maxIterations, colonySize, convergenceIterations, ConstructionGraphBuilder.BuildBNConstructionGraph(trainingset.Metadata), problem)
{
this._trainingSet = trainingset;
this._dependencies = maxDependencies;
this._dependenciesProbability = new double[maxDependencies];
}
public override void Initialize()
{
List <VariableTypeAssignment> variableTypes = new List <VariableTypeAssignment>();
foreach (DataMining.Data.Attribute attribute in this._trainingSet.Metadata.Attributes)
{
variableTypes.Add(new VariableTypeAssignment(attribute.Index, VariableType.Effect));
}
this.SetInputVariableTypes(variableTypes);
((BayesianClassificationQualityEvaluator)this._problem.SolutionQualityEvaluator).ValidationSet = this._trainingSet;
((CMICalculator)this.Problem.HeuristicsCalculator).Dataset = this._trainingSet;
this._graph = ConstructionGraphBuilder.BuildBNConstructionGraph(_trainingSet.Metadata);
base.Initialize();
for (int index = 0; index < this._dependenciesProbability.Length; index++)
{
this._dependenciesProbability[index] = 1 / (double)this._dependenciesProbability.Length;
}
}