组合学习模型
1.使用lasso回归进行特征选择
《基于Lasso和BP神经网络的组合预测及其应用———以居民消费支出预测为例》
*为了消除各变量之间的量纲的影响,且比较容易得到平稳序列,需要对部分数据进行对数处理。
*单变量神经网络,滚动预测法 疑问:神经网络(机器学习算法)在怎么利用多变量数据预测未来值?
Ensemble learning
组合预测
2.将时间序列预测转化成有监督学习(非常好的几篇博客)
https://machinelearningmastery.com/start-here/#process
https://machinelearningmastery.com/time-series-forecasting-supervised-learning/
https://machinelearningmastery.com/convert-time-series-supervised-learning-problem-python/
https://machinelearningmastery.com/backtest-machine-learning-models-time-series-forecasting/
https://machinelearningmastery.com/multivariate-time-series-forecasting-lstms-keras/
https://en.wikipedia.org/wiki/Multicollinearity
https://machinelearningmastery.com/understand-machine-learning-data-descriptive-statistics-python/
https://machinelearningmastery.com/gentle-introduction-autocorrelation-partial-autocorrelation/
窗口法和时间步方法的比较
https://machinelearningmastery.com/time-series-prediction-lstm-recurrent-neural-networks-python-keras/
1)LSTMs for Univariate Time Series Forecasting:https://machinelearningmastery.com/time-series-forecasting-long-short-term-memory-network-python/
2)LSTMs for Multivariate Time Series Forecasting:https://machinelearningmastery.com/multivariate-time-series-forecasting-lstms-keras/
3)LSTMs for Multi-Step Time Series Forecasting:https://machinelearningmastery.com/multi-step-time-series-forecasting-long-short-term-memory-networks-python
How to Update LSTM Networks During Training for Time Series Forecasting
https://machinelearningmastery.com/update-lstm-networks-training-time-series-forecasting/
独热码
https://machinelearningmastery.com/how-to-one-hot-encode-sequence-data-in-python/
2.学习率怎么调
作者:Nutastray
链接:https://www.zhihu.com/question/56152826/answer/147994162
来源:知乎
https://www.jianshu.com/p/d99b83f4c1a6
4.在keras中如何对参数进行调优https://blog.csdn.net/shingle_/article/details/52653588
9.使用深度学习LSTM时间序列预测
http://www.jakob-aungiers.com/articles/a/LSTM-Neural-Network-for-Time-Series-Prediction
10.LSTM超参数调试注意事项
https://blog.csdn.net/chenzhi1992/article/details/77005876
11.lstm股价预测
Stock Market Predictions with LSTM in Python:https://www.datacamp.com/community/tutorials/lstm-python-stock-market
12.scikit-learn线性回归算法库小结
https://www.cnblogs.com/pinard/p/6026343.html
13.用深度学习每次得到的结果都不一样,怎么办?
https://machinelearningmastery.com/reproducible-results-neural-networks-keras/
https://www.leiphone.com/news/201706/zt4Dm491Ol58C8Mc.html
14.Python时间序列数据的基本特征工程
https://machinelearningmastery.com/basic-feature-engineering-time-series-data-python/