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Purifying data by machine learning with certainty levels
Proceedings of the Third International Workshop on Reliability, Availability, and Security - WRAS '10
A fundamental paradigm used for autonomic computing, self-managing systems, and decision-making under uncertainty and faults is machine learning. Machine learning uses a data-set, or a set of data-items. A data-item is a vector of feature values and a classification. Occasionally these data sets include misleading data items that were either introduced by input device malfunctions, or were maliciously inserted to lead the machine learning to wrong conclusions. A reliable learning algorithm mustdoi:10.1145/1953563.1953567 dblp:conf/podc/DolevLY10 fatcat:5tsho3pw6vcdddhkvxp2ykupjm