public Data(DataTable dataSet)
{
this.OriginalDataSet = dataSet;
this.DataSet = ConvertNumericData(dataSet.Copy());
this.Decisions = FindDecisions();
AttributeValuePairs = AttributeValuePair.GetAttributeValuePairs(DataSet);
Characteristic = new Characteristic(this);
MaximalConsistent = new MaximalConsistent(this);
ConditionalProbability = ProbApprox.GetConditionalProbability(this);
}
public static Dictionary <string, List <int> > GetConceptApprox(MaximalConsistent maximalConsistent, List <Probabilities <List <int> > > conditionalProb, float alpha)
{
Dictionary <string, List <int> > tempApprox = new Dictionary <string, List <int> >();
foreach (var prob in conditionalProb)
{
var charIds = prob.ConditionalProb.Where(t => t.Value >= alpha).Select(u => u.Key).ToList();
// Union all Characteristic Sets
var approx = charIds.SelectMany(u => u).Distinct().ToList(); //var approx = characteristic.CharacteristicSets.Where(set => charIds.Contains(set.Key)).SelectMany(u => u.Value).Distinct().ToList();
approx.Sort();
tempApprox.Add(prob.Decision, approx);
}
return(tempApprox);
}
public static List <Probabilities <List <int> > > ComputeConditionalProbability(Data data, MaximalConsistent maximalConsistent)
{
List <Probabilities <List <int> > > conditionalProb = new List <Probabilities <List <int> > >();
foreach (var decision in data.Decisions)
{
Dictionary <List <int>, float> tempProbs = new Dictionary <List <int>, float>();
foreach (var maximalBlocks in maximalConsistent.MaximalBlocks)
{
tempProbs.Add(maximalBlocks, FindProbability(maximalBlocks, decision.Value));
}
Probabilities <List <int> > tempProbabilities = new Probabilities <List <int> >
{
Decision = decision.Key,
DecisionSet = decision.Value,
ConditionalProb = tempProbs
};
conditionalProb.Add(tempProbabilities);
}
return(conditionalProb);
}
