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  • Lift (data mining) - Wikipedia

    OverviewExampleSee also

    In data mining and association rule learning, lift is a measure of the performance of a targeting model (association rule) at predicting or classifying cases as having an enhanced response (with respect to the population as a whole), measured against a random choice targeting model. A targeting model is doing a good job if the response within the target is much better than the average for the population as a whole. Lift is simply the ratio of these values: target response divided by average response. For example, suppose a population has an average response rate of 5%, but a certain model (

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    In data mining and association rule learning, lift is a measure of the performance of a targeting model (association rule) at predicting or classifying cases as having an enhanced response (with respect to the population as a whole), measured against a random choice targeting model. A targeting model is doing a good job if the response within the target is much better than the average for the population as a whole. Lift is simply the ratio of these values: target response divided by average response. For example, suppose a population has an average response rate of 5%, but a certain model (or rule) has identified a segment with a response rate of 20%. Then that segment would have a lift of 4.0 (20%/5%). Typically, the modeller seeks to divide the population into quantiles, and rank the quantiles by lift. Organizations can then consider each quantile, and by weighing the predicted response rate (and associated financial benefit) against the cost, they can decide whether to market to that quantile or not. The lift curve can also be considered a variation on the receiver operating characteristic (ROC) curve, and is also known in econometrics as the Lorenz or power curve. $${\displaystyle lift={\frac {P(A\cap B)}{P(A)*P(B)}}}$$

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  • Data mining — Lift in an association rule

    The lift is a measure for the deviation of the rule from the model of statistic independency of the rule body and rule head. The lift is a value between 0 and infinity: A lift value greater than 1 indicates that the rule body and the rule head appear more often together than expected, this means that the occurrence of the rule body has a ...

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  • Simple Data Mining: Lift

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  • Lift Analysis – A Data Scientist’s Secret Weapon

    But What is Lift Exactly? Until now, we only looked at nice charts. But usually you're interested in the lift score as well. The definition is pretty simple: lift = ( predicted rate / average rate ) rate in our situation refers to the churn rate, but might as well be a conversion rate, response rate etc.

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  • What is the lift in Data Mining? - Quora

    In the data mining concept, lift is a measure of performance and used specifically in association rule. It also used in different fields such as statistics. And it is defined as This measure can only take positive values. The value 1 indicates ant...

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    The lift, also referred to as the interestingness measure, takes this into account by incorporating the prior probability of the rule consequent as follows: A lift value less (larger) than 1 indicates a negative (positive) dependence or substitution (complementary) effect.

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