Implementation of the Bayesian Noise Reduction (BNR) algorithm
'libbnr' implements of the Bayesian Noise Reduction (BNR) algorithm. All samples of text contain some degree of noise (data irrelevant to accurate statistical analysis of the sample where removal of the data would result in a cleaner analysis). The Bayesian noise reduction algorithm ensures cleaner machine learning by providing more useful data, which ultimately leads to better sample analysis. With the noisy data removed from the sample, only data relevant to the classification is left. 'libbnr' can be linked in with a classifier and called using the standard C interface.
released on 26 July 2004
|License||Verified by||Verified on||Notes|
|GPLv2orlater||Janet Casey||22 July 2004|
Leaders and contributors
|Jonathan A. Zdziarski||Maintainer|
Resources and communication
This entry (in part or in whole) was last reviewed on 21 January 2017.
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