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One feature that classification algorithms typically lack is the ability to know what they do not know. With this knowledge an algorithm would be able to operate in any domain and only produce results when it is confident that data is within nominal conditions. Otherwise, it could generate warning messages or request more appropriate training material. We present an unsupervised approach capable of...
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