Suppose you are trying to predict which customers will make a purchase. If you have 1,000 customers in the data set, and 100 of them have made a purchase, then selecting 250 customers randomly should lead, on average, to 25 observed purchases.
Now, suppose that, instead of selecting 250 individuals randomly, you select the 250 individuals who have the highest likelihood of making a purchase (as predicted by the model). If 90 of these individuals have indeed made a purchase, it means that the model performs significantly better than chance.
In this instance, the model performs (90 / 25) – 1 = 260% better than a random selection. We say that the lift of the model is 3.6. A lift of 1.0 means there is no improvement compared to a random selection. The higher the lift, the better the model.
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