public static List <AssociationRule> Mine(ItemsetCollection db, ItemsetCollection L, double confidenceThreshold)
{
List <AssociationRule> allRules = new List <AssociationRule>();
foreach (Itemset itemset in L)
{
ItemsetCollection subsets = Bit.FindSubsets(itemset, 0); //get all subsets
foreach (Itemset subset in subsets)
{
double confidence = (db.FindSupport(itemset) / db.FindSupport(subset)) * 100.0;
if (confidence >= confidenceThreshold)
{
AssociationRule rule = new AssociationRule();
rule.X.AddRange(subset);
rule.Y.AddRange(itemset.Remove(subset));
rule.Support = db.FindSupport(itemset);
rule.Confidence = confidence;
if (rule.X.Count > 0 && rule.Y.Count > 0)
{
allRules.Add(rule);
}
}
}
}
return(allRules);
}
public static ItemsetCollection DoApriori(ItemsetCollection db, double supportThreshold)
{
Itemset I = db.GetUniqueItems();
ItemsetCollection L = new ItemsetCollection(); //resultant large itemsets
ItemsetCollection Li = new ItemsetCollection(); //large itemset in each iteration
ItemsetCollection Ci = new ItemsetCollection(); //pruned itemset in each iteration
//first iteration (1-item itemsets)
foreach (string item in I)
{
Ci.Add(new Itemset()
{
item
});
}
//next iterations
int k = 2;
while (Ci.Count != 0)
{
//set Li from Ci (pruning)
Li.Clear();
foreach (Itemset itemset in Ci)
{
itemset.Support = db.FindSupport(itemset);
if (itemset.Support >= supportThreshold)
{
Li.Add(itemset);
L.Add(itemset);
}
}
//set Ci for next iteration (find supersets of Li)
Ci.Clear();
Ci.AddRange(Bit.FindSubsets(Li.GetUniqueItems(), k)); //get k-item subsets
k += 1;
}
return(L);
}