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instantiating a series of machine-generated contexts to serve as a means of contrast. This makes it possible to identify text that is out of context using a form of pattern consistency checking. BNR attempts to solve the problem commonly referred to as "Bayesian Noise" which, in its simplest definition, refers to irrelevant data present in a message being classified. Bayesian Noise Reduction dubs irrelevant text in order to provide cleaner classification and is implemented as a pre-filter to existing language classification functions. PR: ports/78159 Submitted by: Ion-Mihai "IOnut" Tetcu <itetcu@people.tecnik93.com>
3 lines
97 B
Plaintext
3 lines
97 B
Plaintext
MD5 (libbnr-2.0.3.tar.gz) = 4bbff2cab5d352c6d3bdbb706037e40e
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SIZE (libbnr-2.0.3.tar.gz) = 293199
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