Limits on Learning Machine Accuracy Imposed by Data Quality

Corinna Cortes, L. D. Jackel, and Wan-Ping Chiang, AT&T Bell Laboratories

Random errors and insufficiencies in databases limit the performance of any classifier trained from and applied to the database. In this paper we propose a method to estimate the limiting performance of classifiers imposed by the database. We demonstrate this technique on the task of predicting failure in telecommunication paths.


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