走班排课系统

import pandas as pd

from sklearn.model_selection import train_test_split

from sklearn.linear_model import LinearRegression

# 加载学生成绩数据

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

# 数据预处理

X = data[['Hours_Studied', 'Previous_Scores']]

y = data['Final_Score']

# 划分训练集和测试集

X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)

# 训练线性回归模型

model = LinearRegression()

model.fit(X_train, y_train)

# 预测测试集结果

predictions = model.predict(X_test)

print(predictions)

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from sklearn.ensemble import IsolationForest

# 使用孤立森林进行异常检测

iso_forest = IsolationForest(contamination=0.05)

anomalies = iso_forest.fit_predict(X)

# 输出异常值索引

anomaly_indices = [i for i, val in enumerate(anomalies) if val == -1]

print("异常学生索引:", anomaly_indices)

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