TsFormer is a toolbox that implement transformer models on Time series data
- data preprocess
- gefcom2014
- uci
- ETT
- dataloader
- dataloaders
- models
- rnn
- lstm
- GRU
- ESN
- CNN
- TCN
- transformer
- informer
- autoformer
- TODO
- Spacetimeformer
- SCINet
- Deep learning for time series forecasting
- PyTorch Forecasting
- tsai
- flow-forecast
- train and evaluate
python -u run_autoformer.py \
--is_training 1 \
--root_path ./data/electricity/ \
--data_path electricity.csv \
--model_id ECL \
--model informer \
--data custom \
--features S \
--seq_len 96 \
--label_len 48 \
--pred_len 96 \
--e_layers 2 \
--d_layers 1 \
--factor 3 \
--enc_in 1 \
--dec_in 1 \
--c_out 1 \
--embed fixed \
--des 'Exp' \
--itr 1
mse:0.2755982279777527, mae:0.3857262134552002,rmse:0.524974524974823, mape:1.9572646617889404, mspe:238.20448303222656
python -u run_autoformer.py \
--is_training 1 \
--root_path ./data/electricity/ \
--data_path electricity.csv \
--model_id ECL \
--model informer \
--data custom \
--features S \
--seq_len 96 \
--label_len 48 \
--pred_len 96 \
--e_layers 2 \
--d_layers 1 \
--factor 3 \
--enc_in 1 \
--dec_in 1 \
--c_out 1 \
--embed timeF \
--des 'Exp' \
--itr 1
mse:0.22287048399448395, mae:0.3356129825115204,rmse:0.4720916152000427, mape:1.6913783550262451, mspe:260.3700866699219
python -u run_autoformer.py \
--is_training 1 \
--root_path ./data/electricity/ \
--data_path electricity.csv \
--model_id ECL \
--model transformer \
--data custom \
--features S \
--seq_len 96 \
--label_len 48 \
--pred_len 96 \
--e_layers 2 \
--d_layers 1 \
--factor 3 \
--enc_in 1 \
--dec_in 1 \
--c_out 1 \
--embed timeF \
--des 'Exp' \
--itr
mse:0.284598171710968, mae:0.38772597908973694,rmse:0.5334774255752563, mape:2.1156060695648193, mspe:381.4866943359375
python -u run_autoformer.py \
--is_training 1 \
--root_path ./data/electricity/ \
--data_path electricity.csv \
--model_id ECL \
--model autoformer \
--data custom \
--features M \
--seq_len 96 \
--label_len 48 \
--pred_len 96 \
--e_layers 2 \
--d_layers 1 \
--factor 3 \
--enc_in 321 \
--dec_in 321 \
--c_out 321 \
--des 'Exp' \
--itr 1
mse:0.2043592780828476, mae:0.3170555830001831,rmse:0.45206114649772644, mape:3.2521157264709473, mspe:414847.125