The Lift Curve option provides another plot to display the predictive ability of a partition model. The lift curve plots the lift versus the portion of the observations. Each predicted response level defines a portion of the observations that are greater than or equal to that predicted response. The lift value is the ratio of the proportion of positive responses in that portion to the overall proportion of positive responses.
Figure 4.17 Lift Curve
Figure 4.18 Lift Table for Lift Curve
Figure 4.18 provides a table of values to demonstrate the calculation of Lift and Portion used for the High lift curve shown in Figure 4.17. A partition model with five splits was built to predict the response, Y Binary. Y Binary has two levels: Low and High. The lift curve is based on 309 observations. There are 83 High responses for an overall rate of 0.27.
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Prob High: The five predicted values from the partition model for the High response level.
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Portion: N > Prob High divided by 309.
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N High in Portion: The number of High responses in the portion.
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Portion High: N High in Portion divided by N > Prob High.
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Lift: Portion High divided by 0.27.
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