Page 82 - Demo

%u062c%u0645%u064a%u0639 %u0627%u0644%u062d%u0642%u0648%u0642 %u0645%u062d%u0641%u0648%u0638%u0629 %u0640 %u0627%u0625%u0644%u0639%u062a%u062f%u0627%u0621 %u0639%u0649%u0644 %u062d%u0642 %u0627%u0645%u0644%u0624%u0644%u0641 %u0628%u0627%u0644%u0646%u0633%u062e %u0623%u0648 %u0627%u0644%u0637%u0628%u0627%u0639%u0629 %u064a%u0639%u0631%u0636 %u0641%u0627%u0639%u0644%u0647 %u0644%u0644%u0645%u0633%u0627%u0626%u0644%u0629 %u0627%u0644%u0642%u0627%u0646%u0648%u0646%u064a%u062982Frequent patterns can be partitioned into subsets according to f-list:-a) F-list = f-c-a-b-m-p b) Patterns containing p c) Patterns having m but no p d) Patterns having c but no a nor b, m, p to find patterns having P From P-conditional Database: steps: 1-Starting at the frequent item header table in the FP-tree 2-Traverse the FP-tree by following the link of each frequent item p 3-Accumulate all of transformed prefix paths of item p to form p%u2019s conditional pattern base From Conditional Pattern-bases to Conditional FP-trees: For each pattern-base: accumulate the count for each item in the base,construct the FP-tree for the frequent items of the pattern base.