ALdataset

ALdataset是由香港城市大学的Xueying Zhan和Antoni Bert Chan提出的一个基准数据集，用于池基础主动学习研究。该数据集包含20个公共数据集，涵盖了多种属性，如数据规模、维度、类别数等，旨在为主动学习算法提供一个全面的评估平台。这些数据集来源于不同的文献和领域，用于验证主动学习模型在不同任务上的有效性。通过这些数据集，研究者可以比较和分析不同主动学习策略的性能，从而推动主动学习领域的发展。

The ALdataset is a benchmark dataset proposed by Xueying Zhan and Antoni Bert Chan from City University of Hong Kong for pool-based active learning research. It contains 20 public datasets with multiple attributes including data scale, dimensionality, number of classes, etc., aiming to provide a comprehensive evaluation platform for active learning algorithms. These datasets are sourced from various literatures and domains, and are used to validate the effectiveness of active learning models across different tasks. With these datasets, researchers can compare and analyze the performance of different active learning strategies, thereby advancing the development of the active learning field.