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zhangxu0307
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Description

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

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# 321,201
Python
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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

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