Forecasting Models¶
Regression Models¶
- Baseline Models (LocalForecastingModel)
- Global Baseline Models (GlobalForecastingModel)
- Statistical Models (LocalForecastingModel)
- SKLearn-Like Models (GlobalForecastingModel)
- PyTorch (Lightning)-based Models (GlobalForecastingModel)
- Ensemble Models (GlobalForecastingModel)
- Conformal Models (GlobalForecastingModel)
Classification Models¶
- SKLearn-Like Models (GlobalForecastingModel)
- ARIMA
- Baseline Models
- Block Recurrent Neural Networks
- CatBoost Models
- Conformal Models
- D-Linear
- Exponential Smoothing
- Fast Fourier Transform
- Global Baseline Models (Naive)
- Kalman Filter Forecaster
- LightGBM Models
- Linear Regression Model
- N-BEATS
- N-HiTS
- N-Linear
- Facebook Prophet
- Random Forest
- Regression Ensemble Model
- Recurrent Neural Networks
- AutoARIMA
- AutoCES
- AutoETS
- AutoMFLES
- AutoTBATS
- AutoTheta
- Croston Method
- StatsForecastModel
- TBATS
- SKLearn-Like Models
- Temporal Convolutional Network
- Temporal Fusion Transformer (TFT)
- Theta Method
- Time-series Dense Encoder (TiDE)
- Transformer Model
- Time-Series Mixer (TSMixer)
- VARIMA
- XGBoost Models