Limits on Learning Machine Accuracy Imposed by Data Quality
Corinna Cortes, L. D. Jackel, Wan-Ping Chiang · 1994
Random errors and insufficiencies in databases limit the perfor-mance of any classifier trained from and applied to the database. In this paper we propose a method to estimate the limiting perfor-mance of classifiers imposed by the database. We demonstrate this technique on the task of predicting failure in telecommunication paths. 1