1. FPtree/FPGrowth

2. FP-Tree/FP-Growth Algorithm Use a compressed representation of the database using an FP-tree Then use a recursive divide-and-conquer approach to mine the frequent itemsets.

3. Building the FP-Tree 1.Scan data to determine the support count of each item. Infrequent items are discarded, while the frequent items are sorted in decreasing support counts. 2.Make a second pass over the data to construct the FP­ tree. As the transactions are read, before being processed, their items are sorted according to the above frequency order.

4. First scan – determine frequent 1-itemsets, then build header B8 A7 C7 D5 E3

5. FP-tree construction null B:1 A:1 After reading TID=1: After reading TID=2: null B:2 A:1 C:1 D:1

6. FP-Tree Construction Transaction Database Header table B:8 A:5 null C:3 D:1 A:2 C:1 D:1 E:1 D:1 E:1C:3 D:1 E:1 Chain pointers help in quickly finding all the paths of the tree containing some given item.

7. FP-Tree size Size of FP­tree is typically smaller than the size of the uncompressed data. –Because many transactions often share a few items in common. Best­case scenario: –All transactions have the same set of items, and the FP­tree contains only a single branch of nodes. Worst­case scenario: –Every transaction has a unique set of items. As none of the transactions have any items in common, the size of the FP­tree is effectively the same as the size of the original data. Size of FP­tree also depends on how the items are ordered. –If the ordering scheme in the preceding example is reversed, i.e., from lowest to highest support item, the resulting FP­tree is denser.

8. FP-Growth FP­growth generates frequent itemsets by exploring the FP-tree in a bottom­up fashion. It starts with the less frequent item, in this example, E. Then, the algorithm looks for frequent itemsets ending in E first, followed by D, C, A, and finally, B. –We can derive the frequent itemsets ending with E, by examining only the paths containing node E. These paths can be accessed rapidly using the pointers associated with node E.

9. Paths containing node E B:1 null C:1 A:2 C:1 D:1 E:1 D:1 E:1 B:8 A:5 null C:3 D:1 A:2 C:1 D:1 E:1 D:1 E:1C:3 D:1 E:1

10. Conditional FP-Tree for E FP-Growth builds a conditional FP-Tree for E, which is the tree of itemsets ending in E. It is not the tree obtained in the previous slide as result of deleting nodes from the original tree. Why? Because the order of the items can change. –Now, C has a higher count than B.

11. Suffix E We continue recursively. Base of recursion: When the tree has a single path only. FI: E The set of paths ending in E. Insert each path (after truncating E) into a new tree. (New) Header table C:1 null Conditional FP-Tree for suffix E A2 C2 D2 B:1 null C:1 A:2 C:1 D:1 E:1 D:1 E:1 A:2 C:1 D:1 B doesn’t survive because its support is 1, which is lower than minsupport of 2.

12. Steps of Building Conditional FP-Trees 1.Find the paths containing on focus item. 2.Read the tree to determine the new counts of the items along those paths. Build a new header. 3.Read again the tree. Insert the paths in the conditional FP-Tree according to the new order.

13. Suffix DE We have reached the base of recursion. FI: DE, ADE The set of paths, from the E- conditional FP-Tree, ending in D. Insert each path (after truncating D) into a new tree. (New) Header table null A:2 The conditional FP-Tree for suffix DE A2 null A:2 C:1 D:1

14. Base of Recursion We continue recursively on the conditional FP-Tree. Base case of recursion: when the tree is just a single path. –Then, we just produce all the subsets of the items on this path merged with the corresponding suffix.

15. Suffix CE We have reached the base of recursion. FI: CE The set of paths, from the E- conditional FP-Tree, ending in C. Insert each path (after truncating C) into a new tree. (New) Header table null The conditional FP-Tree for suffix CE C:1 null A:1 C:1

16. Suffix AE We have reached the base of recursion. FI: AE The set of paths, from the E- conditional FP-Tree, ending in A. Insert each path (after truncating A) into a new tree. (New) Header table null The conditional FP-Tree for suffix AE null A:2

17. Suffix D We continue recursively. Base of recursion: When the tree has a single path only. FI: D The set of paths ending in D. Insert each path (after truncating D) into a new tree. (New) Header table A:4 null B:2 B:1 C:1 Conditional FP-Tree for suffix D A4 B3 C3 B:3 A:2 null C:1 D:1 A:2 C:1 D:1 C:1 D:1 C:1

18. Suffix CD We continue recursively. Base of recursion: When the tree has a single path only. FI: CD The set of paths, from the D-conditional FP-Tree, ending in C. Insert each path (after truncating C) into a new tree. (New) Header table A:4 null B:2 C:1 Conditional FP-Tree for suffix CD A2 B2 C:1 B:1 C:1 A:2 null B:1

19. Suffix BCD We have reached the base of recursion. FI: BCD The set of paths from the CD-conditional FP-Tree, ending in B. Insert each path (after truncating B) into a new tree. (New) Header table Conditional FP-Tree for suffix CDB null A:2 null B:1

20. Suffix ACD We have reached the base of recursion. FI: ACD The set of paths from the CD-conditional FP-Tree, ending in A. Insert each path (after truncating B) into a new tree. (New) Header table Conditional FP-Tree for suffix ACD null

21. Suffix C We continue recursively. Base of recursion: When the tree has a single path only. FI: C The set of paths ending in C. Insert each path (after truncating C) into a new tree. (New) Header table Conditional FP-Tree for suffix C B6 A4 B:6 A:3 null C:3 A:1 C:1 C:3B:6 A:3 null A:1

22. Suffix AC We have reached the base of recursion. FI: AC, BAC The set of paths from the C-conditional FP-Tree, ending in A. Insert each path (after truncating A) into a new tree. (New) Header table Conditional FP-Tree for suffix AC B3 B:3 null B:6 A:3 null A:1

23. Suffix BC We have reached the base of recursion. FI: BC The set of paths from the C-conditional FP-Tree, ending in B. Insert each path (after truncating B) into a new tree. (New) Header table Conditional FP-Tree for suffix BC B3 null B:6 null

24. Suffix A We have reached the base of recursion. FI: A, BA The set of paths ending in A. Insert each path (after truncating A) into a new tree. (New) Header table Conditional FP-Tree for suffix A B5 B:5 null B:5 A:5 null A:2

25. Suffix B We have reached the base of recursion. FI: B The set of paths ending in B. Insert each path (after truncating B) into a new tree. (New) Header table Conditional FP-Tree for suffix B null B:8 null