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information projection : ウィキペディア英語版
information projection
In information theory, the information projection or I-projection of a probability distribution ''q'' onto a set of distributions ''P'' is
:p^
* = \underset \operatorname_} is the Kullback–Leibler divergence from ''p'' to ''q''. Viewing the Kullback–Leibler divergence as a measure of distance, the I-projection p^
* is the "closest" distribution to ''q'' of all the distributions in ''P''.
The I-projection is useful in setting up information geometry, noteably because of the following inequality:
\operatorname___{\mathrm{KL}}(p^
*||r)
==See also==

*Sanov's theorem

抄文引用元・出典: フリー百科事典『 ウィキペディア(Wikipedia)
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