Minibeans

A subsample of the Koklu & Ozkan (2020) dry beans dataset produced by imaging a total of 13,611 grains from 7 varieties of dry beans. The original dataset contains 13,611 observations, but here we include a random subsample of 1000. See https://doi.org/10.24432/C50S4B for original complete dataset.The dataset is also available from the ggEDA R package (`ggEDA::minibeans`).If you use please cite the original publication:Koklu, M, and IA Ozkan. 2020. Multiclass Classification of Dry Beans Using Computer Vision and Machine Learning Techniques. Computers and Electronics in Agriculture, 174: 105507. doi: 10.1016/j.compag.2020.105507, https://doi.org/10.24432/C50S4BAnd also the UCI Machine Learning Repository where the dataset:Dry Bean [Dataset]. (2020). UCI Machine Learning Repository. https://doi.org/10.24432/C50S4B.本数据集为Koklu与Ozkan（2020）发布的干豆数据集的子采样版本，该原始数据集通过对7个品种共计13611粒干豆进行成像采集得到。原始数据集共包含13611条观测样本，本次研究仅随机选取其中1000条作为本次使用的子样本。完整原始数据集可通过链接https://doi.org/10.24432/C50S4B获取，同时本数据集亦可通过ggEDA R包的`ggEDA::minibeans`接口获取。 若使用本数据集，请引用以下原始文献： Koklu, M 与 Ozkan, I A. 2020. 基于计算机视觉与机器学习技术的干豆多分类任务. 《农业计算机与电子学》, 174: 105507. doi: 10.1016/j.compag.2020.105507, https://doi.org/10.24432/C50S4B 同时，请引用UCI机器学习库（UCI Machine Learning Repository）的如下条目：干豆数据集 [Dry Bean Dataset]. (2020). UCI机器学习库（UCI Machine Learning Repository）. https://doi.org/10.24432/C50S4B.