Add sklearn.metrics.cumulative_gain_curve and sklearn.metrics.lift_curve

Description

I recently added plot_cumulative_gain and plot_lift_curve methods to https://github.com/reiinakano/scikit-plot. To do this, I built an adhoc version of cumulative_gain_curve closely following the sklearn.metrics.roc_curve interface at https://github.com/reiinakano/scikit-plot/blob/master/scikitplot/helpers.py#L157. Let me know if sklearn.metrics.cumulative_gain_curve is something you’d be interested in adding into scikit-learn. I could add example docs for plotting gain and lift curves as well.

Reference I followed for lift and gain: https://www.ibm.com/support/knowledgecenter/en/SSLVMB_23.0.0/spss/tutorials/mlp_bankloan_outputtype_02.html

[GuillemGSubies]

Any progress here? An intuitive explanation of the lift curve can be found here:

http://www2.cs.uregina.ca/~dbd/cs831/notes/lift_chart/lift_chart.html

It is like “how much better than the random model I am doing at each percentile”

[lorentzenchr]

TLDR

+1 for inclusion of the gain curve/CAP. Naming should reflect different strands of literature: cumulative accuracy profile (CAP) [2][4], concentration curve [3], cumulative lift curve [5]. It should work for binary classification as well as regression (models for the expectation).

Some more background

The cumulative gains curve is the same as the Cumulative Accuracy Profile (CAP), see [1] and [4]. From [2]

Moody’s uses Cumulative Accuracy Profiles (CAP), to make visual, qualitative assessments of model performance. While similar tools exist under a variety of different names (lift-curves, dubbed-curves, receiver-operator curves, power curves, etc.).

References: [1] Tasche 2006 “Validation of internal rating systems and PD estimates” https://arxiv.org/pdf/physics/0606071.pdf [2] Soběhart, J.R., Keenan, S.C., & Stein, R.M. (2000). “Benchmarking Quantitative Default Risk Models: A Validation Methodology” [3] Denuit, M., Trufin, J. (2021). “Lorenz curve, Gini coefficient, and Tweedie dominance for autocalibrated predictors” https://dial.uclouvain.be/pr/boreal/object/boreal%3A254535/datastream/PDF_01/view [4] https://www.listendata.com/2019/09/gini-cumulative-accuracy-profile-auc.html [5] Ling C, Li C (1998). “Data Mining for Direct Marketing: Problems and solutions.” In Proceedings of the Fourth International Conference on Knowledge Discovery and Data Mining, pp. 73–79.