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);
}
public Apriori()
{
ItemsetCollection data = new ItemsetCollection();
List <itemset> temp = db.itemsets.ToList();
foreach (var item in temp)
{
Itemset item11 = new Itemset();
List <string> itemsetsList = item.items.Split(',').ToList();
foreach (string sp in itemsetsList)
{
item11.Add(sp);
}
data.Add(item11);
}
StringBuilder s = new StringBuilder();
Itemset uniqueItems = data.GetUniqueItems();
s.Append(uniqueItems + "<br/>");
//test apriori
ItemsetCollection L = AprioriMining.DoApriori(data, 30.0);
s.Append("<br/>" + L.Count + " itemsets in L<br/>");
foreach (Itemset i in L)
{
s.Append(i + "<br/>");
}
//test mining
List <AssociationRule> allRules = AprioriMining.Mine(data, L, 70.0);
rules = allRules;
s.Append("<br/>" + allRules.Count + " rules<br/>");
foreach (AssociationRule rule in allRules)
{
s.Append(rule + "<br/>");
}
str = s.ToString();
}