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Oct, 2023
基于池化的主动学习与合适的拓扑区域
Pool-Based Active Learning with Proper Topological Regions
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Lies Hadjadj, Emilie Devijver, Remi Molinier, Massih-Reza Amini
TL;DR
基于拓扑数据分析的合适拓扑区域，提出了一个对多类别分类任务中的基于池的主动学习策略的元方法，通过在各种基准数据集上的实证研究表明，该方法在竞争力上与文献中的经典方法相当。
Abstract
machine learning
methods usually rely on large sample size to have good performance, while it is difficult to provide labeled set in many applications. Pool-based
active learning
methods are there to detect, amon
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