Limits on Learning Machine Accuracy Imposed by Data Quality

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.

• Type: Conference
• Year: 1995
• Where: KDD
• Authors: Corinna Cortes, Lawrence D. Jackel, Wan-Ping Chiang
• Keywords: Data Mining, KDD 1995, Performance, Random Errors, Telecommunication Paths