统一消息系统

import pandas as pd

from sklearn.feature_extraction.text import CountVectorizer

from sklearn.naive_bayes import MultinomialNB

# 示例数据

data = {'text': ['考试时间已确定', '社团招新开始', '校园新闻：新建图书馆'],

'label': ['考试', '社团', '新闻']}

df = pd.DataFrame(data)

vectorizer = CountVectorizer()

X = vectorizer.fit_transform(df['text'])

y = df['label']

model = MultinomialNB()

model.fit(X, y)

new_text = ["下周有考试"]

predicted = model.predict(vectorizer.transform(new_text))

print("预测类别:", predicted[0])