Publicly Available Datasets from UCI, Penn, and OpenML

该数据集汇总了在67个公开可用的数据集上进行的实验，这些数据集包含分类数据。这些数据集的平均特征数为31.2，平均实例数为6045.3。规模上，这些数据集的特征数量从2到58不等，实例数量从87到58000不等。研究的任务是评估决策树中的解释冗余。

This dataset aggregates experiments conducted on 67 publicly available classification datasets. The average number of features across these datasets is 31.2, with an average of 6045.3 instances. In terms of scale, the feature counts of these datasets range from 2 to 58, while the instance counts vary from 87 to 58000. The research task is to evaluate explanatory redundancy in decision trees.