书接前文。跟ROC类似，Lift（提升）和Gain（增益）也一样能简单地从以前的Confusion Matrix以及Sensitivity、Specificity等信息中推导而来，也有跟一个baseline model的比较，然后也是很容易画出来，很容易解释。以下先修知识，包括所需的数据集：
*更多，见
http://cos.name/2009/02/measure-classification-model-performance-lift-gain/
del.icio.us Tags: Lift,Gain,Confusion Matrix,Logistic回归,SAS,Sensitiveity,Specificity,分类模型,数据挖掘,混淆矩阵,Kolmogorov-Smirnov,Lorentz Curve
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