- Year not given
Lift measure with example
Short answer
Lift = P(A∪B)/(P(A)P(B)) = confidence/support(B). Measures correlation: >1 positive, =1 independent, <1 negative. Example: 6 transactions, 4 Chips, 3 Coke, 3 both. Support=0.5, P(Chips)=0.667, P(Coke)=0.5, Lift=1.5. Indicates Coke makes Chips 1.5x more likely.
Define the measure "Lift" with suitable example. What does it signify?
Lift is a correlation measure of an association rule that tells whether the occurrence of A and B together is more (or less) than expected if they were independent. Support and confidence alone can be misleading, since a rule can have high confidence only because B is itself very common.
Definition
For the rule A → B:
Lift(A, B) = P(A ∪ B) / (P(A)·P(B)) = confidence(A → B) / support(B)
What it signifies
| Lift value | Meaning |
|---|---|
| > 1 | A and B are positively correlated: A makes B more likely |
| = 1 | A and B are independent; the rule is not useful |
| < 1 | A and B are negatively correlated: A makes B less likely |
The larger the lift, the stronger the association; lift is symmetric: lift(A, B) = lift(B, A).
Example
Among 6 transactions of a shop: 4 contain Chips, 3 contain Coke, and 3 contain both.
- Support(Chips ∪ Coke) = 3/6 = 0.5
- P(Chips) = 4/6 = 0.667; P(Coke) = 3/6 = 0.5
- Lift = 0.5/(0.667 × 0.5) = 1.5
Lift 1.5 > 1: buying Coke makes Chips 1.5 times more likely than average, so they are positively correlated.
Misleading-rule example: of 10000 customers, 6000 buy computer games, 7500 buy videos, 4000 buy both. Rule games → videos has confidence 4000/6000 = 66.7% and looks strong, but lift = 0.4/(0.6 × 0.75) = 0.89 < 1: games and videos are actually negatively correlated.
✓ Answer checked by Claude Opus 5.5 (high effort)