/// <summary>
/// Frequent pattern extraction method that implement FPGrowth logic using an
/// iterative pattern growth approach
/// </summary>
/// <param name="allTrans">Total list of input transaction</param>
/// <returns>Frequent ItemSets</returns>
public List <ItemSet> ExtractFrequentPattern(List <Transaction> allTrans)
{
// compute absolute support = relative support * # of transactions
absMinSup = (int)System.Math.Ceiling(allTrans.Count * _minSup);
result = new List <ItemSet>();
//We could have used two stacks instead of these lists!!!
List <FPTree> FPTreeList = new List <FPTree>();
List <FPTree> FPTreeListNext = new List <FPTree>();
List <ItemSet> GivenListNow = new List <ItemSet>();
List <ItemSet> GivenListNext = new List <ItemSet>();
FPTree Next;
ItemSet Given;
ItemSet Beta;
List <ItemSet> wholeTransToItemSet = new List <ItemSet>();
foreach (Transaction trans in allTrans)
{
wholeTransToItemSet.Add(trans.Itemset);
}
FPTree StartFPtree = new FPTree();
StartFPtree.SetMinSup(absMinSup);
//Build the first tree on the whole transaction database list
StartFPtree.BuildFirstTree(wholeTransToItemSet);
//Add the first tree to the list of the fptree to process
FPTreeList.Add(StartFPtree);
//Here our given prefix is null
GivenListNow.Add(new ItemSet());
//Looping on each fptree until there are ones to process
while (FPTreeList.Count > 0)
{
for (int j = 0; j < FPTreeList.Count; j++)
{
Next = FPTreeList[j];
Given = GivenListNow[j];
if (!Next.isEmpty())
{
// If the FPTree we are examining is composed of a single path
// we use an optimization based on path node combination which
// arrest current iteration
if (Next.HasSinglePath)
{
GenerateCombPattern(Next, Given);
}
else
{
// Header table sorting
Next.SortHeaderTable();
//Loop on each header table entry
for (int i = 0; i < Next.GetHTSize(); i++)
{
//New beta ItemSet representing a frequent pattern
Beta = new ItemSet();
//Concatenate with items present in the given ItemSet
foreach (int item in Given.Items)
{
Beta.Add(item);
}
Beta.Add(Next.GetHTItem(i));
Beta.ItemsSupport = Next.GetHTFreq(i);
// Add beta to frequent pattern result
result.Add(Beta);
// Here we generate the so called Conditional FPTree using a projection
// of the original database called Conditional Pattern Base
FPTreeListNext.Add(Next.CreateFPtree(i));
// Insert current beta in next given list
GivenListNext.Add(Beta);
}
FPTreeList[j] = null;
GivenListNow[j] = null;
}
}
}
FPTreeList.Clear();
GivenListNow.Clear();
for (int j = 0; j < GivenListNext.Count; j++)
{
FPTreeList.Add(FPTreeListNext[j]);
GivenListNow.Add(GivenListNext[j]);
GivenListNext[j] = null;
FPTreeListNext[j] = null;
}
GivenListNext.Clear();
FPTreeListNext.Clear();
}
return(result);
}