When Does Active Learning Work?
When Does Active Learning Work?
复制标题
主动学习什么时候有效？
DOI：
10.1007/978-3-642-41398-8_16
复制
发表时间：
2013
期刊：
影响因子：
--
通讯作者：
C. Anagnostopoulos
中科院分区：
文献类型：
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作者：
Lewis P. G. Evans;N. Adams;C. Anagnostopoulos
当标签昂贵或稀缺时，主动学习人工智能方法寻求提高分类器的性能。我们考虑两个核心问题：AL在哪里工作？这有多大帮助呢？为了解决这些问题，本文对主动学习进行了全面的实验模拟研究。我们考虑了各种任务、分类器和其他AL因素，以呈现在不同环境下AL表现的广泛探索。需要一种精确的方法来量化性能，以便知道AL何时起作用。因此，在这项实验研究的背景下，我们还提出了一种详细的方法来处理评估AL表现的复杂性。
Active Learning AL methods seek to improve classifier performance when labels are expensive or scarce. We consider two central questions: Where does AL work? How much does it help? To address these questions, a comprehensive experimental simulation study of Active Learning is presented. We consider a variety of tasks, classifiers and other AL factors, to present a broad exploration of AL performance in various settings. A precise way to quantify performance is needed in order to know when AL works. Thus we also present a detailed methodology for tackling the complexities of assessing AL performance in the context of this experimental study.