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翻訳と辞書　辞書検索 [ 開発暫定版 ] スポンサード リンク Margin Infused Relaxed Algorithm ： ウィキペディア英語版 Margin Infused Relaxed Algorithm Margin-infused relaxed algorithm (MIRA)〔 〕 is a machine learning algorithm, an online algorithm for multiclass classification problems. It is designed to learn a set of parameters (vector or matrix) by processing all the given training examples one-by-one and updating the parameters according to each training example, so that the current training example is classified correctly with a margin against incorrect classifications at least as large as their loss.〔 〕 The change of the parameters is kept as small as possible. A two-class version called binary MIRA〔 simplifies the algorithm by not requiring the solution of a quadratic programming problem (see below). When used in a one-vs.-all configuration, binary MIRA can be extended to a multiclass learner that approximates full MIRA, but may be faster to train. The flow of the algorithm〔Watanabe, T. et al (2007): "Online Large Margin Training for Statistical Machine Translation". In: ''Proceedings of the 2007 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning'', 764–773.〕〔Bohnet, B. (2009): ''Efficient Parsing of Syntactic and Semantic Dependency Structures''. Proceedings of Conference on Natural Language Learning (CoNLL), Boulder, 67–72.〕 looks as follows: Input: Training examples $T\; =\; \backslash$ Output: Set of parameters $w$ $i$ ← 0, $w^$ ← 0 for $n$ ← 1 to $N$ for $t$ ← 1 to $|T|$ $w^$ ← update $w^$ according to $\backslash$ $i$ ← $i\; +\; 1$ end for end for return $\backslash frac\; w^\}$ The update step is then formalized as a quadratic programming〔 problem: Find $min\backslash |w^\; -\; w^\backslash |$, so that $score(x\_t,y\_t)\; -\; score(x\_t,y\text{'})\backslash geq\; L(y\_t,y\text{'})\backslash \; \backslash forall\; y\text{'}$, i.e. the score of the current correct training $y$ must be greater than the score of any other possible $y\text{'}$ by at least the loss (number of errors) of that $y\text{'}$ in comparison to $y$. ==References== 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「Margin Infused Relaxed Algorithm」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.