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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>
10 lines
185 B
Plaintext
10 lines
185 B
Plaintext
include/libbnr/bnr.h
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include/libbnr/hash.h
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include/libbnr/list.h
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lib/libbnr.a
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lib/libbnr.so
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lib/libbnr.so.2
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%%EXAMPLESDIR%%/example.c
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@dirrm share/examples/libbnr
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@dirrm include/libbnr
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