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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 One-class classification ： ウィキペディア英語版 One-class classification In machine learning, one-class classification, also known as unary classification, tries to ''identify'' objects of a specific class amongst all objects, by learning from a training set containing only the objects of that class. This is different from and more difficult than the traditional classification problem, which tries to ''distinguish between'' two or more classes with the training set containing objects from all the classes. An example is the classification of the operational status of a nuclear plant as 'normal':〔(Tax, D. (2001) One-class classification: Concept-learning in the absence of counter-examples. Doctoral Dissertation, University of Delft, The Netherlands. )〕 In this scenario, there are (fortunately) few or no examples of catastrophic system states, only the statistics of normal operation are known. The term One-class classification was coined by Moya & Hush (1996)〔Moya, M. and Hush, D. (1996). "Network constraints and multi- objective optimization for one-class classification". ''Neural Networks'', 9(3):463–474. 〕 and many applications can be found in scientific literature, for example outlier detection, anomaly detection, novelty detection. A similar problem is PU learning, in which a binary classifier is learned in a semi-supervised way from only ''positive'' and ''unlabeled'' samples. ==PU learning== In PU learning, two sets of samples are assumed to be available for training: the positive set $P$ and a ''mixed set'' $U$, which is assumed to contain both positive and negative samples, but without these being labeled as such. This contrasts with other forms of semisupervised learning, where it is assumed that a labeled set containing examples of both classes is available in addition to unlabeled samples. A variety of techniques exist to adapt supervised classifiers to the PU learning setting, including variants of the EM algorithm. PU learning has been successfully applied to text, time series, and bioinformatics tasks. 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「One-class classification」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.