翻訳と辞書 Words near each other ・ Log line ・ Log Logo ・ Log management ・ Log management knowledge base ・ Log monitor ・ Log nad Škofjo Loko ・ Log Pile, Pennsylvania ・ Log pod Mangartom ・ Log pod Mangartom Mosque ・ Log pond ・ Log pri Brezovici ・ Log pri Mlinšah ・ Log pri Polhovem Gradcu ・ Log pri Vrhovem ・ Log pri Žužemberku ・ Log probability ・ Log Revolution ・ Log rotation ・ Log Run ・ Log scaler ・ Log School House (Yellowknife) ・ Log series (Westminster Press) ・ Log shipping ・ Log splitter ・ Log structure ・ Log sum inequality ・ Log trigger ・ Log v Bohinju ・ Log Valley, Saskatchewan ・ Log wind profile Dictionary Lists mini英和辞書 mini和英辞書 Webster 1913 Latin-English FOLDOC Wikipedia English ウィキペディア

翻訳と辞書　辞書検索 [ 開発暫定版 ] スポンサード リンク Log probability ： ウィキペディア英語版 Log probability In computer science, the use of log probabilities means representing probabilities in logarithmic space, instead of the the standard $(1)$ interval. This has practical advantages, because of the way in which computers approximate real numbers, and because computers can perform addition more efficiently than multiplication. A log probability is simply the logarithm of a probability. The logarithm function is not defined for zero, so log probabilities can only represent non-zero probabilities. Since the logarithm of a number in $]0,\; 1]$ interval is negative, often the negative log probabilities are used. In that case the log probabilities in the following formulas will be inverted. Any base can be selected for the logarithm. : $x\text{'}\; =\; \backslash log(x)\; \backslash in\; \backslash mathbb$ : $y\text{'}\; =\; \backslash log(y)\; \backslash in\; \backslash mathbb$ The product of probabilities $x\; \backslash cdot\; y$ corresponds to addition in logarithmic space. : $\backslash log(x\; \backslash cdot\; y)\; =\; \backslash log(x)\; +\; \backslash log(y)\; =\; x\text{'}\; +\; y\text{'}$. The sum of probabilities $x\; +\; y$ is a bit more involved to compute in logarithmic space, requiring the computation of one exponent and one logarithm. : $\backslash log(x\; +\; y)$ : $=\; \backslash log(x\; +\; x\; \backslash cdot\; y\; /\; x)$ : $=\; \backslash log(x\; +\; x\; \backslash cdot\; \backslash exp(\backslash log(y\; /\; x)))$ : $=\; \backslash log(x\; \backslash cdot\; (1\; +\; \backslash exp(\backslash log(y)\; -\; \backslash log(x)))$ : $=\; \backslash log(x)\; +\; \backslash log(1\; +\; \backslash exp(\backslash log(y)\; -\; \backslash log(x)))$ : $=\; x\text{'}\; +\; \backslash log(1\; +\; \backslash exp(y\text{'}\; -\; x\text{'}))$ However, in many applications a multiplication of probabilities (giving the probability of all independent events occurring) is used more often than their addition (giving the probability of at least one of them occurring). Additionally, the cost of computing the addition can be avoided in some situations by simply using the highest probability as an approximation. Since probabilities are non-negative this gives a lower bound. Representing probabilities in this way has two main advantages: # Speed. Since multiplication is more expensive than addition, taking the product of a high number of probabilities is faster if they are represented in log form. (The conversion to log form is expensive, but is only incurred once.) # Accuracy. The use of log probabilities improves numerical stability, when the probabilities are very small. The use of log probabilities is widespread in several fields of computer science such as information theory and natural language processing as it represents the surprisal, the minimum length of the message that specifies the outcome in an optimally efficient code. 抄文引用元・出典: フリー百科事典『 ウィキペディア（Wikipedia）』 ■ウィキペディアで「Log probability」の詳細全文を読む スポンサード リンク 翻訳と辞書 : 翻訳のためのインターネットリソース Copyright(C) kotoba.ne.jp 1997-2016. All Rights Reserved.