构建基于招生服务系统的智能职业推荐平台

import pandas as pd

# 读取数据

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

学生迎新系统

# 删除缺失值

data.dropna(inplace=True)

# 检查是否有重复记录

data.drop_duplicates(inplace=True)

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from sklearn.neighbors import KNeighborsClassifier

from sklearn.preprocessing import LabelEncoder

# 初始化编码器

label_encoder = LabelEncoder()

# 对职业类别进行编码

data['career'] = label_encoder.fit_transform(data['career'])

# 特征选择

features = ['math_score', 'english_score', 'interest']

X = data[features]

y = data['career']

# 训练模型

knn = KNeighborsClassifier(n_neighbors=5)

knn.fit(X, y)

# 预测新学生的推荐职业

new_student = [[90, 85, 1]]

predicted_career = knn.predict(new_student)

print("推荐职业:", label_encoder.inverse_transform(predicted_career))

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