Credal Bird-10

Most datasets used for classification use hard labels. Credal Bird-10 was labeled uncertainly and imprecisely by contributors during crowdsourcing campaigns. Resulting in richer labels, modeled with the theory of belief funtions, which generalizes several reasoning frameworks with uncertainty. These datasets can be used with classical models using hard labels but also with probabilistic, fuzzy or even evidential models. Dataset: 10 classes, 200 observations, 30 features (or raw pictures) When using the dataset please cite : A. Hoarau, C. Thierry, A. Martin, J.-C. Dubois, Y. Le Gall, "Datasets with rich labels for machine learning", in: FUZZ-IEEE, 2023. Credal Bird-10 dataset ├── data │ ├── classes.csv: Classes of the dataset │ ├── X.csv: Features of the dataset │ ├── X_512.csv: Learge 512 features vector of the dataset │ ├── X_pictures.csv: Raw features (Pictures themselves) │ ├── y.csv: Rich labels │ └── y_true.csv: True labels └── extra ├── y_hard.csv: Hard labels given during a new campaign ├── DATA_imperfect.csv: Imperfect answers given during the campaign ├── ITERATION_imperfect.csv: Imperfect 2nd step answers given during the campaign ├── EVENT_imperfect.csv: Contributors events ├── ID_imperfect.csv: Contributors IDs └── DATA_perfect.csv: Precise answers given during a new campaign Credal Dog-7: https://data.mendeley.com/datasets/4hz3wx6wm5 Credal Dog-4: https://data.mendeley.com/datasets/44zpkbrpxb Credal Dog-2: https://data.mendeley.com/datasets/95mmjfrsyh Credal Bird-2: https://data.mendeley.com/datasets/v8k6c5s9cy当前多数用于分类任务的数据集均采用硬标签（hard labels）。Credal Bird-10数据集在众包任务中由参与者标注时带有不确定性与不精确性，最终生成了更为丰富的标签，并基于信任函数理论（theory of belief functions）进行建模——该理论可泛化多种不确定性推理框架。此类数据集既可配合使用硬标签的经典模型进行训练，也可适配概率模型、模糊模型乃至证据推理模型。 数据集概况：共10个类别、200条样本、30维特征（或原始图像数据）。 使用本数据集时，请引用以下文献：A. Hoarau、C. Thierry、A. Martin、J.-C. Dubois、Y. Le Gall，"Datasets with rich labels for machine learning"，收录于：FUZZ-IEEE 2023。 ### Credal Bird-10 数据集文件结构 ├── data/ │ ├── classes.csv：数据集类别信息 │ ├── X.csv：数据集特征数据 │ ├── X_512.csv：512维特征向量数据集 │ ├── X_pictures.csv：原始图像特征（即原始图片本身） │ ├── y.csv：富标签数据 │ └── y_true.csv：真实标签数据 └── extra/ ├── y_hard.csv：新一轮众包任务中生成的硬标签 ├── DATA_imperfect.csv：本次众包任务中收集的不精确标注结果 ├── ITERATION_imperfect.csv：本次众包任务第二轮生成的不精确标注结果 ├── EVENT_imperfect.csv：参与者标注事件记录 ├── ID_imperfect.csv：参与者身份标识 └── DATA_perfect.csv：新一轮众包任务中收集的精确标注结果 此外还有以下同系列数据集： - Credal Dog-7：https://data.mendeley.com/datasets/4hz3wx6wm5 - Credal Dog-4：https://data.mendeley.com/datasets/44zpkbrpxb - Credal Dog-2：https://data.mendeley.com/datasets/95mmjfrsyh - Credal Bird-2：https://data.mendeley.com/datasets/v8k6c5s9cy