Well, the cumulative expected profit should not be a linear curve given the Profit/Loss matrix defined in the example (where profit and loss are constant for every case). In fact, in such constant profit/loss cases, the expected profit of a single case has a linear relationship with the predicted probability; therefore accumulating its value over the top score cases will give a non-linear relationship with the predicted probability, which will most likely also generate a non-linear relationship with the predicted probability quantiles (as the quantiles are the ones used on the horizontal axis of the graph).
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Use this tutorial as a handy guide to weigh the pros and cons of these commonly used machine learning algorithms.
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