Public datasets for GBSR

We use a total of 16 datasets, detailed descriptions of which are provided in Table II. Among them, 11 datasets are from the UCI database, the DLBCL-Harvard dataset is from the ELVIRA biomedical database, Yale and ORLare face image datasets, and lung and ALLAML are biological datasets. The bankDirectMarketing and smartGridStabilityAugmented datasets are from the Kaggle platform. These datasets are commonly used for attribute reduction and sourced from various application domains; they exhibit a wide range of sample sizes and attribute counts. The diverse nature of these datasets helps demonstrate the effectiveness and generalization performance of the algorithms. In the experiments, all data are normalized to the [0, 1] range to eliminate the influence of dimensions. 

搜集汇总

背景与挑战

背景概述

这是一个由16个数据集组成的集合，用于属性约简和特征选择研究，数据集来自UCI、ELVIRA生物医学数据库、人脸图像数据集和Kaggle等来源，包含不同规模（样本数72至60000，属性数8至7129）的多样数据，并经过归一化处理以评估算法性能。