yolowinnn/The-Research-on-Logistic-Regression-Model-for-SMS-Spam-Classification-

项目基于SMS Spam Collection数据集,构建并优化了逻辑回归模型进行垃圾短信自动分类。 采用TF-IDF方法进行特征提取,使用梯度下降算法训练模型,并通过5折交叉验证和网格搜索优化超参 数。最终,模型准确率达到0.96,精确度、召回率和F1值均表现优异,研究还通过ROC曲线和精确度 召回率曲线进一步评估了分类效果。该模型在垃圾短信分类任务中展现了较高的性能与实际实用价值

12
/ 100
Experimental

No commits in the last 6 months.

No License Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 4 / 25
Maturity 8 / 25
Community 0 / 25

How are scores calculated?

Stars

6

Forks

Language

Python

License

Last pushed

Dec 17, 2024

Commits (30d)

0

Get this data via API

curl "https://pt-edge.onrender.com/api/v1/quality/nlp/yolowinnn/The-Research-on-Logistic-Regression-Model-for-SMS-Spam-Classification-"

Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.