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Apriori on t1-t5 with rules
Short answer
Apriori with min_sup=2 yields 15 frequent itemsets, largest {A,B,C,E}. 37 strong rules (conf≥60%) include A→C, B→E (100%), B→C (75%), A→B (66.7%), sorted by confidence.
Identify the candidate and large item sets of the following transaction table. Use Apriori algorithm with minimum support 2. Also, indicate association rules generated, underline the strong ones and sort them by confidence. (min_conf = 60%)
| Transaction id | Items |
|---|---|
| t1 | {A, C, D} |
| t2 | {B, C, E} |
| t3 | {A, B, C, E} |
| t4 | {B, E} |
| t5 | {A, B, C, E} |
Minimum support count = 2, minimum confidence = 60%. Transactions: t1 {A, C, D}; t2 {B, C, E}; t3 {A, B, C, E}; t4 {B, E}; t5 {A, B, C, E}.
Frequent itemsets by Apriori
C₁: A 3, B 4, C 4, D 1, E 4 → D is removed. L₁ = {A, B, C, E}.
C₂ and L₂
| Itemset | Count | Frequent? |
|---|---|---|
| A, B | 2 | Yes |
| A, C | 3 | Yes |
| A, E | 2 | Yes |
| B, C | 3 | Yes |
| B, E | 4 | Yes |
| C, E | 3 | Yes |
C₃ and L₃ (all subsets frequent, no pruning)
| Itemset | Count | Frequent? |
|---|---|---|
| A, B, C | 2 | Yes |
| A, B, E | 2 | Yes |
| A, C, E | 2 | Yes |
| B, C, E | 3 | Yes |
C₄ and L₄: {A, B, C, E} count 2 → frequent. No C₅.
Total frequent itemsets: 4 + 6 + 4 + 1 = 15.
Association rules
Every non-empty proper subset X of each frequent itemset L (size ≥ 2) gives X → L − X with confidence = count(L)/count(X). Rules are sorted by confidence; the strong rules (≥ 60%) are in bold.
| Rule | Support count | Confidence | Strong? |
|---|---|---|---|
| A → C | 3 | 3/3 = 100.0% | Yes |
| B → E | 4 | 4/4 = 100.0% | Yes |
| E → B | 4 | 4/4 = 100.0% | Yes |
| A, B → C | 2 | 2/2 = 100.0% | Yes |
| A, B → C, E | 2 | 2/2 = 100.0% | Yes |
| A, B → E | 2 | 2/2 = 100.0% | Yes |
| A, E → B | 2 | 2/2 = 100.0% | Yes |
| A, E → B, C | 2 | 2/2 = 100.0% | Yes |
| A, E → C | 2 | 2/2 = 100.0% | Yes |
| B, C → E | 3 | 3/3 = 100.0% | Yes |
| C, E → B | 3 | 3/3 = 100.0% | Yes |
| A, B, C → E | 2 | 2/2 = 100.0% | Yes |
| A, B, E → C | 2 | 2/2 = 100.0% | Yes |
| A, C, E → B | 2 | 2/2 = 100.0% | Yes |
| B → C | 3 | 3/4 = 75.0% | Yes |
| B → C, E | 3 | 3/4 = 75.0% | Yes |
| C → A | 3 | 3/4 = 75.0% | Yes |
| C → B | 3 | 3/4 = 75.0% | Yes |
| C → B, E | 3 | 3/4 = 75.0% | Yes |
| C → E | 3 | 3/4 = 75.0% | Yes |
| E → B, C | 3 | 3/4 = 75.0% | Yes |
| E → C | 3 | 3/4 = 75.0% | Yes |
| B, E → C | 3 | 3/4 = 75.0% | Yes |
| A → B | 2 | 2/3 = 66.7% | Yes |
| A → B, C | 2 | 2/3 = 66.7% | Yes |
| A → B, C, E | 2 | 2/3 = 66.7% | Yes |
| A → B, E | 2 | 2/3 = 66.7% | Yes |
| A → C, E | 2 | 2/3 = 66.7% | Yes |
| A → E | 2 | 2/3 = 66.7% | Yes |
| A, C → B | 2 | 2/3 = 66.7% | Yes |
| A, C → B, E | 2 | 2/3 = 66.7% | Yes |
| A, C → E | 2 | 2/3 = 66.7% | Yes |
| B, C → A | 2 | 2/3 = 66.7% | Yes |
| B, C → A, E | 2 | 2/3 = 66.7% | Yes |
| C, E → A | 2 | 2/3 = 66.7% | Yes |
| C, E → A, B | 2 | 2/3 = 66.7% | Yes |
| B, C, E → A | 2 | 2/3 = 66.7% | Yes |
| B → A | 2 | 2/4 = 50.0% | No |
| B → A, C | 2 | 2/4 = 50.0% | No |
| B → A, C, E | 2 | 2/4 = 50.0% | No |
| B → A, E | 2 | 2/4 = 50.0% | No |
| C → A, B | 2 | 2/4 = 50.0% | No |
| C → A, B, E | 2 | 2/4 = 50.0% | No |
| C → A, E | 2 | 2/4 = 50.0% | No |
| E → A | 2 | 2/4 = 50.0% | No |
| E → A, B | 2 | 2/4 = 50.0% | No |
| E → A, B, C | 2 | 2/4 = 50.0% | No |
| E → A, C | 2 | 2/4 = 50.0% | No |
| B, E → A | 2 | 2/4 = 50.0% | No |
| B, E → A, C | 2 | 2/4 = 50.0% | No |
Answer: 15 frequent itemsets (largest {A, B, C, E}). 50 rules are generated (12 from the 2-itemsets, 24 from the 3-itemsets and 14 from the 4-itemset). Of these, 37 are strong (14 at 100%, 9 at 75% and 14 at 66.7%), and the other 13 have confidence 50%.
✓ Answer checked by Claude Opus 5.5 (high effort)
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