针对具有验证延迟的数据流的预期贝叶斯分类法

IF 16.4 1区化学 Q1 CHEMISTRY, MULTIDISCIPLINARY

Accounts of Chemical Research Pub Date : 2024-02-21 DOI:10.1080/02664763.2024.2319222

Vera Hofer, Georg Krempl, Dominik Lang

引用次数: 0

摘要

大多数现有的非稳态数据流自适应分类算法都需要最近的标签数据来更新。而这种近期标签往往是缺失的。对于数据流分类来说，这就需要有新的标签。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Anticipative Bayesian classification for data streams with verification latency

Most of the existing adaptive classification algorithms in non-stationary data streams require recent labelled data for their updates. Such recent labels are often missing. For stream classificatio...

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来源期刊

Accounts of Chemical Research 化学-化学综合

CiteScore

31.40

自引率

1.10%

发文量

312

审稿时长

2 months

期刊介绍： Accounts of Chemical Research presents short, concise and critical articles offering easy-to-read overviews of basic research and applications in all areas of chemistry and biochemistry. These short reviews focus on research from the author’s own laboratory and are designed to teach the reader about a research project. In addition, Accounts of Chemical Research publishes commentaries that give an informed opinion on a current research problem. Special Issues online are devoted to a single topic of unusual activity and significance. Accounts of Chemical Research replaces the traditional article abstract with an article "Conspectus." These entries synopsize the research affording the reader a closer look at the content and significance of an article. Through this provision of a more detailed description of the article contents, the Conspectus enhances the article's discoverability by search engines and the exposure for the research.