This project is a Financial Text Sentiment Analyzer built in Python, combining traditional ML models (TF-IDF + Logistic Regression, SVM, Naive Bayes) with state-of-the-art NLP (FinBERT). It also ...

我们以4972条真实客户数据为样本，通过Python工具链（pandas、scikit-learn等）完成从数据清洗到模型部署的闭环，创新点在于将RFM客户价值分析思想与机器学习模型融合，实现“分群-预测-挽留”的精细化运营。

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