Regression Error Characteristic Curves

By Jinbo Bi, Kristin P. Bennett. International Conference on Machine Learning, 2003

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Evaluating prediction systems in software project estimation (2012, background): “Likewise Bi and Bennett [1] suggest the use of the sample mean as the baseline for their proposed anologue of the ROC curve, namely a regression error characteristic curve.”
A Survey of Predictive Modeling on Imbalanced Domains (2016, methodology): “Another relevant effort towards the adaptation of the concept of ROC curves to regression tasks was made by Bi and Bennett [2003] with the proposal of Regression Error Characteristic ( REC ) curves that provide a graphical representation of the cumulative distribution function (cdf) of the error of…”
Using Data Mining for Wine Quality Assessment (2009, methodology): “The regression error characteristic (REC) curve [1] is also used to compare regression models, with the ideal model presenting an area of 1.”
Modeling wine preferences by data mining from physicochemical properties (2009, background): “Certification prevents the illegal adulteration of wines (to safeguard human health) and assures quality for the wine market.”
A data mining approach to predict forest fires using meteorological data (2007, background): “Another possibility to compare regression models is the Regression Error Characteristic (REC) curve [2], which plots the error tolerance ( x - axis), given in terms of the absolute deviation, versus the percentage of points predicted within the tolerance ( y -axis).”