锦中招生管理系统

import pandas as pd

from sklearn.feature_extraction.text import TfidfVectorizer

from sklearn.naive_bayes import MultinomialNB

# 假设我们有一个包含申请材料的数据集

data = pd.read_csv('applications.csv')

# 提取文本和标签

texts = data['text']

labels = data['label']

# 特征提取

vectorizer = TfidfVectorizer()

X = vectorizer.fit_transform(texts)

# 训练模型

model = MultinomialNB()

model.fit(X, labels)

# 预测新申请

new_application = ["该学生在数学竞赛中获得一等奖"]

new_X = vectorizer.transform(new_application)

prediction = model.predict(new_X)

print("预测结果:", prediction[0])