Open AccessROC curve, lift chart and calibration plot
Author(s) -
Miha Vuk,
Tomaž Curk
Publication year - 2006
Publication title -
metodološki zvezki
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.127
H-Index - 7
eISSN - 1854-0031
pISSN - 1854-0023
DOI - 10.51936/noqf3710
Subject(s) - lift (data mining) , plot (graphics) , chart , computer science , calibration , data mining , visualization , measure (data warehouse) , machine learning , artificial intelligence , mathematics , statistics
This paper presents ROC curve, lift chart and calibration plot, three well known graphical techniques that are useful for evaluating the quality of classification models used in data mining and machine learning. Each technique, normally used and studied separately, defines its own measure of classification quality and its visualization. Here, we give a brief survey of the methods and establish a common mathematical framework which adds some new aspects, explanations and interrelations between these techniques. We conclude with an empirical evaluation and a few examples on how to use the presented techniques to boost classification accuracy.