Model Monitor (M²): Evaluating, Comparing, and Monitoring Models

Raeder, Troy; Chawla, Nitesh V.
July 2009
Journal of Machine Learning Research;7/1/2009, Vol. 10 Issue 7, p1387
Academic Journal
This paper presents Model Monitor (M²), a Java toolkit for robustly evaluating machine learning algorithms in the presence of changing data distributions. M² provides a simple and intuitive framework in which users can evaluate classifiers under hypothesized shifts in distribution and therefore determine the best model (or models) for their data under a number of potential scenarios. Additionally, M² is fully integrated with the WEKA machine learning environment, so that a variety of commodity classifiers can be used if desired.


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