| 摘要 |
The Naïve Bayes Classifier predicts the classification of a set of data based on the features of that data and a series of counts reflecting the information obtained from prior data sets, with one count per feature per class. An external boost can be applied to the counts generated by the NBC to account for external information. Such a boost is added to the counts generated by the NBC, and the boosted counts are then used by the NBC. A boost can be applied to some or all of the counts and the boost for each count can be applied independently. Likewise, the counts can be periodically aged by multiplying the counts with an aging factor of between 0 and 1 per period. Aging factors can be applied uniformly across all counts, or can be individually applied, enabling some counts to age more than others.
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