from sklearn.linearmodel import LinearRegression model = LinearRegression() model.fit(aggregateddata[['timestamp']], aggregated_data['temperature'])
深度学习分析
from keras.models import Sequential model = Sequential() model.add(LSTM(50, inputshape=(1, 1))) model.add(Dense(1)) model.compile(loss='meansquarederror', optimizer='adam') model.fit(aggregateddata[['timestamp']], aggregateddata['temperature'], epochs=100, batchsize=1) ```
5. 未来发展趋势与挑战