Multiclass and labeled dataset containing 3290 samples of cleanwares and 16450 of malwares. Five classes of malware (backdoor, rootkit, trojan, virus and worm) with 3290 samples of each class were lab

DataCite Commons2025-06-01 更新100

harperlucy2023/autotrain-data-consunmer-complain-multiclass-classification

消费者投诉

多类分类

该数据集是通过AutoTrain自动处理的，用于消费者投诉的多类别分类项目。数据集的语言为英语，任务类别为文本分类。数据集包含三个字段：feat_Unnamed: 0、text和target，其中target是一个类别标签。数据集被划分为训练集和验证集，分别包含20663和5167个样本。

Hugging Face2023-01-16 更新220

Feature set selection result for multiclass classification using 5-fold cross-validation in development set.

多类分类

特征选择

Feature set selection result for multiclass classification using 5-fold cross-validation in development set.

Figshare2020-11-18 更新100