Class Distribution Before and After Data Augmentation.

NIAID Data Ecosystem2026-05-02 收录

数据增强评估

类别不平衡

数据链接：

https://figshare.com/articles/dataset/Class_Distribution_Before_and_After_Data_Augmentation_/29933179 数据链接链接失效反馈

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资源简介：

Class Distribution Before and After Data Augmentation.

创建时间：

2025-08-18

CLIMB

类别不平衡

数据挖掘

CLIMB是一个针对表格数据上的类别不平衡学习的综合基准，包含73个真实世界的表格数据集，涵盖了广泛的领域和失衡水平。该数据集旨在为类别不平衡学习提供基准，并支持不同类别不平衡学习算法之间的轻松实现和比较。数据集的创建基于严格的非平凡性和现实性标准，确保了数据集的真实性和实用性。数据集包括多种算法实现，如重采样、成本敏感学习和基于集成的方法。数据集还包含了一个统一的API设计，详细的文档和严格的代

arXiv2025-05-23 更新320

Public datasets.

交易欺诈

类别不平衡

The rapid growth of digital payments exacerbates the challenges in Financial Transaction Fraud Detection (FTFD). These challenges stem primarily from an extreme class imbalance, where legitimate trans

Figshare2026-02-20 更新40

wanling_tsai_exp_dataset

二分类任务基准

数据增强评估

This dataset contains four collections of samples stored in NumPy .npy format, designed for binary classification tasks. Each dataset folder includes two subfolders, train\/ and test\/, which further

IEEE30

Artificial and Real dataset with different concept drift type and imbalance ratio

概念漂移检测

类别不平衡

The zip file contains both real and artificial datasets having different concept drift type and imbalance ratio. The real datasets are usually used as a benchmark for concept drift problems and they a

NIAID Data Ecosystem120

Classification results of deep learning algorithms on dataset D1 after expansion.

深度学习分类

数据增强评估

Classification results of deep learning algorithms on dataset D1 after expansion.

Figshare2025-06-10 更新40