地球资源数据云——数据资源详情
假新闻检测数据集
该数据集《Fake News Detection Dataset》主要用于二分类任务，数据形态以图像为主，应用场景偏向医疗健康。 题目说明：A large - scale, balanced, and high - quality dataset for practicing fake news. 任务类型：图像二分类。 建议流程：先检查类别分布与脏样本，再用迁移学习（如 ResNet/EfficientNet）建立基线。 评估建议：使用分层切分或交叉验证，优先关注 F1、Recall、AUC 等分类指标。 可用文件：fake_news_dataset.csv。 Fake News Detection Dataset Overview This dataset is designed for practicing fake news detection using machine learning and natural language processing (NLP) techniques. It includes a rich collection of 20,000 news articles, carefully generated to simulate real - world data scenarios. Each record contains metadata about the article and a label indicating whether the news is real or fake. The dataset also intentionally includes around 5% missing values in some fields to simulate the challenges of handling incomplete data in real - life projects. Columns Description
摘要概览
该数据集《Fake News Detection Dataset》主要用于二分类任务，数据形态以图像为主，应用场景偏向医疗健康。 题目说明：A large - scale, balanced, and high - quality dataset for practicing fake news.
任务类型：图像二分类。
建议流程：先检查类别分布与脏样本，再用迁移学习（如 ResNet/EfficientNet）建立基线。
评估建议：使用分层切分或交叉验证，优先关注 F1、Recall、AUC 等分类指标。
可用文件：fake_news_dataset.csv。
Fake News Detection Dataset
Overview
This dataset is designed for practicing fake news detection using machine learning and natural language processing (NLP) techniques. It includes a rich collection of 20,000 news articles, carefully generated to simulate real - world data scenarios. Each record contains metadata about the article and a label indicating whether the news is real or fake.
The dataset also intentionally includes around 5% missing values in some fields to simulate the challenges of handling incomplete data in real - life projects.
Columns Description