Additive smoothing
In statistics, additive smoothing, also called Laplace smoothing[1] or Lidstone smoothing, is a technique used to smooth count data, eliminating issues caused by certain values having 0 occurrences. Given a set of observation counts
x
=
⟨
x
1
,
x
2
,
…
,
x
d
⟩
{\displaystyle \mathbf {x} =\langle x_{1},x_{2},\ldots ,x_{d}\rangle }
from a
d
{\displaystyle d}
-dimensional multinomial distribution with
N
{\displaystyle N}
trials, a "smoothed" version of the counts gives the estimator
https://en.wikipedia.org/wiki/Additive_smoothing