This document provides an example of building a frequent pattern growth (FP) tree to identify frequent itemsets from a transactional dataset. It includes the following steps: 1) Calculating the frequency of individual items and prioritizing them. 2) Building the FP tree row-by-row from the dataset, incrementing counters for items as they are added. 3) Updating the FP tree as each additional transaction is processed. The end result is a final FP tree that visually represents the frequent patterns found in the data with a minimum support of 2, from which actual frequent itemsets can be extracted.

1. Modern College of Arts, Science & Commerce Ganeshkhind Pune 16.
Department of Computer Science
Data Mining Assignment
FREQUENT PATTERN GROWTH
ALGORITHM EXAMPLE
Prepared by
Ms. Gunshri Patil gunshrisp4955@gmail.com
Ms. Divya Chavda divyachavda429@gmail.com
Ms. Dhanshree Hande dhanshreehande2157@gmail.com
Ms. Madhuri Patil patilmadhuri4488@gmail.com
Guided by
Dr. Dipali Meher
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2. Q. How to Identify Frequent Patterns using FP Tree
Algorithm? Minimum Support=2.
 Given Dataset:
TId Items
1 A,B,C,D
2 A,B,D
3 A,D
4 A,C
5 B,C
6 B,D
7 A,C,D
2

3. Step-1: Find Frequency of Occurrence.
Table 1-Dataset Table 2-Frequency of Occurance
TID Items
1 A,B,C,D
2 A,B,D
3 A,D
4 A,C
5 B,C
6 B,D
7 A,C,D
Itemset Frequency
{A} 5
{B} 4
{C} 4
{D} 5
3

4. Step-2: Prioritize The Items According to it’s Frequency of
Occurrence.
Table 2- Frequency of Occurrence
Itemset Frequency
{A} 5
{B} 4
{C} 4
{D} 5
Priority
1
3
4
2
4

5. Step-3: Order the Items According to Highest Priority.
Ordered Items
A,D,B,C
A,D,B
A,D
A,C
B,C
D,B
A,D,C
TId Items
1 A, B , C , D
2 A , B , D
3 A , D
4 A , C
5 B , C
6 B , D
7 A, C , D
1
1
1
1
1
5

6. Step-4: Draw the FP tree Row by Row.
All FP tree have ‘null’ node as a root node.
Row 1: Attach the items of the Row1 one by
one respectively. i.e A, D,B,C.
and write their occurrences in front
of it.
Figure 1-FP tree for Row 1
Null
A : 1
D : 1
B : 1
C : 1
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7. Step-5: Update the FP tree(Figure 1) Row by Row.
Row 2: The items of Row 2 are A,D,B.
Now, increase their occurrences in front
of it.
Figure 2-FP tree for Row 2
Null
A : 2
D : 2
B : 2
C : 1
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8. Step-6: Update the FP tree(Figure 2) Row by Row.
Row 3: The items of Row 3 are A,D.
Now, increase their occurrences in front
of it.
Figure 3-FP tree for Row 3
Null
A : 3
D : 3
B : 2
C : 1
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9. Step-7: Update the FP tree(Figure 3) Row by Row.
Row 4: In Row 4 we have to visit A,C respectively.
Now, As a result we should draw another
C and connect it to A.
Figure 4-FP tree for Row 4
Null
A : 4
D : 3
B : 2
C : 1
C : 1
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10. Step-7: Update the FP tree(Figure 4) Row by Row.
Row 5: In Row 5 we have to visit B,C respectively.
Now, we have opportunity to draw new
branch from ‘null’ node.
Figure 5-FP tree for Row 5
Null
A : 4
D : 3
B : 2
C : 1
C : 1
B : 1
C : 1
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11. Step-8: Update the FP tree(Figure 5) Row by Row.
Row 6: In Row 6 we have to visit D,B respectively.
Now, we have opportunity to draw new
branch from ‘null’ node.
Figure 6-FP tree for Row 6
Null
A : 4
D : 3
B : 2
C : 1
C : 1
B : 1
C : 1
D : 1
B : 1
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12. Step-9: Update the FP tree(Figure 6) Row by Row.
Row 7: In Row 7 we have to visit A,D,C respectively.
Now, As a result we should draw another
C and connect it to D.
Figure 7-FP tree for Row 7
Null
A : 5
D : 4
B : 2
C : 1
C : 1
B : 1
C : 1
D : 1
B : 1
C : 1
Itemset Frequency
{A} 5
{B} 4
{C} 4
{D} 5
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13. THANK YOU
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