blankhe / time_series_forecasting_pytorch

time series forecasting using pytorch，including ANN,RNN,LSTM,GRU and TSR-RNN，experimental code

time_series_forecasting_pytorch

Experimental source code: Time series forecasting using pytorch，including MLP,RNN,LSTM,GRU, ARIMA, SVR, RF and TSR-RNN models.

Requirements

• python 3.6.3 (Anaconda)
• keras 2.1.2
• PyTorch 1.0.1
• tensorflow-gpu 1.13.1
• sklearn 0.19.1
• numpy 1.15.4
• pandas 0.23.4
• statsmodels 0.9.0
• matplotlib 2.1.0

Code

• ARIMA.py: ARIMA model, iteration version
• Holt_Winters.py Holt-Winters model, only primary version
• eval.py: evaluation metrics, including RMSE,MAE,MAPE and SMAPE.
• NN_forecasting.py:neural networks forecasting
• model.py: neural network models
• train.py: training and predicting of neural network models, including RNN, LSTM, GRU, MLP, TSR-RNN
• ts_decompose.py: time series decomposition
• ts_loader: data loader for neural network models
• ML_forecasting.py: general machine learning models, including SVR and RF
• util.py: data loader

Related Repository

Time Series Forecasting using Keras