Additive smoothing, also known as Laplace smoothing, is a technique used in probability estimates, particularly in natural language processing and statistical modeling, to handle the problem of zero probabilities in categorical data. When estimating probabilities from observed data, especially with limited samples, certain events may not occur at all in the sample, leading to a probability of zero for those events. This can be problematic in applications like language modeling, where a lack of observed data can lead to misleading conclusions or unanticipated behavior.
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