地球资源数据云——数据资源详情

垃圾邮件与火腿电子邮件

发布时间：2026-03-17 14:30:39资源ID：2032010576539324417资源类型：免费

该数据集《Spam Vs Ham Emails》主要用于二分类任务，数据形态以文本为主，应用场景偏向文本内容分析。 题目说明：Email Dataset for Spam Detection 任务类型：文本二分类。 建议流程：先做文本清洗与分词，再比较 TF - IDF+线性模型 与 预训练语言模型。 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：email_spam_dataset.csv。 This dataset consists of a collection of synthetic email messages labeled as spam and ham, created to support supervised learning experiments in email spam filtering. The dataset provides structured textual data for training NLP - based classification models and can be used to test algorithms such as Naive Bayes, Logistic Regression, Support Vector Machines, and deep learning approaches for spam detection.

垃圾邮件与火腿电子邮件

摘要概览

该数据集《Spam Vs Ham Emails》主要用于二分类任务，数据形态以文本为主，应用场景偏向文本内容分析。 题目说明：Email Dataset for Spam Detection

任务类型：文本二分类。

建议流程：先做文本清洗与分词，再比较 TF - IDF+线性模型 与 预训练语言模型。

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：email_spam_dataset.csv。

This dataset consists of a collection of synthetic email messages labeled as spam and ham, created to support supervised learning experiments in email spam filtering.

The dataset provides structured textual data for training NLP - based classification models and can be used to test algorithms such as Naive Bayes, Logistic Regression, Support Vector Machines, and deep learning approaches for spam detection.