翻訳と辞書 Words near each other ・ Prionus lecontei ・ Prionyx ・ Prior ・ Prior (brand) ・ Prior (disambiguation) ・ Prior (surname) ・ Prior Analytics ・ Prior art ・ Prior authorization ・ Prior Castell's Clock ・ Prior Cliff ・ Prior consistent statements and prior inconsistent statements ・ Prior Hall ・ Prior Island ・ Prior Jones ・ Prior knowledge for pattern recognition ・ Prior Lake High School ・ Prior Lake, Minnesota ・ Prior Norge ・ Prior of Ardchattan ・ Prior of Beauly ・ Prior of Blantyre ・ Prior of Canonbie ・ Prior of Christ Church ・ Prior of Coldingham ・ Prior of Crato ・ Prior of Durham ・ Prior of Fogo ・ Prior of Fyvie ・ Prior of Inchmahome 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 Prior knowledge for pattern recognition ： ウィキペディア英語版 Prior knowledge for pattern recognition Pattern recognition is a very active field of research intimately bound to machine learning. Also known as classification or statistical classification, pattern recognition aims at building a classifier that can determine the class of an input pattern. This procedure, known as training, corresponds to learning an unknown decision function based only on a set of input-output pairs $(\backslash boldsymbol\_i,y\_i)$ that form the training data (or training set). Nonetheless, in real world applications such as character recognition, a certain amount of information on the problem is usually known beforehand. The incorporation of this prior knowledge into the training is the key element that will allow an increase of performance in many applications. == Definition == Prior knowledge〔B. Scholkopf and A. Smola, "Learning with Kernels", MIT Press 2002.〕 refers to all information about the problem available in addition to the training data. However, in this most general form, determining a model from a finite set of samples without prior knowledge is an ill-posed problem, in the sense that a unique model may not exist. Many classifiers incorporate the general smoothness assumption that a test pattern similar to one of the training samples tends to be assigned to the same class. The importance of prior knowledge in machine learning is suggested by its role in search and optimization. Loosely, the no free lunch theorem states that all search algorithms have the same average performance over all problems, and thus implies that to gain in performance on a certain application one must use a specialized algorithm that includes some prior knowledge about the problem. The different types of prior knowledge encountered in pattern recognition are now regrouped under two main categories: class-invariance and knowledge on the data. 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「Prior knowledge for pattern recognition」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.