Auto ML Forecast
| Tech Name | Technique Description | Module (Language) | |
|---|---|---|---|
| 1 | AutoGluon | Automated Machine Learning | Python | 
Machine Learning Models
| Tech Name | Technique Description | Module (Language) | |
|---|---|---|---|
| 1 | XGBOOST | eXtreme Gradient Boosting | Python | 
| 2 | LIGHTGBM | Light Gradient-Boosting Machine | Python | 
| 3 | RANDOM_FOREST | Random Forest (RF) | Python | 
| 4 | PROPHET | Facebook Prophet | Python | 
AI Models (Deep Learning)
| Tech Name | Technique Description | Module (Language) | |
|---|---|---|---|
| 1 | MULTILAYER_PERCEPTRON | Multilayer Perceptron (MLP) | Python | 
| 2 | RNN | Recurrent Neural Network | Python (TensorFlow / PyTorch) | 
| 3 | BlockRNN | Deep RNN for Time Series Forecast | Python (Darts / PyTorch) | 
Statistical Models
| Tech Name | Technique Description | Module (Language) | |
|---|---|---|---|
| 1 | ARIMA_FORECAST | ARIMA Model | R | 
| 2 | AUTOARIMA_FORECAST | Auto Arima | R | 
| 3 | AUTOHWS_FORECAST | Auto Holt-Winters Seasonal (HWS) | R | 
| 4 | AUTOREG_FORECAST | Autoregressive (AR) Forecasting | R | 
| 5 | BATS_FORECAST | BATS (Box-Cox transformation, ARMA errors, Trend, and Seasonal components) | R | 
| 6 | CROSTON_FORECAST | Croston’s Method | R | 
| 7 | DYNAMIC_REGRESSION | Dynamic Regression Model | R | 
| 8 | HWS_FORECAST | Holt-Winters Seasonal (HWS) Method | R | 
| 9 | SNAIVE_FORECAST | The Seasonal Naïve forecast | R | 
| 10 | STL_FORECAST | STL (Seasonal-Trend Decomposition using LOESS) Forecasting | R | 
| 11 | TBATS_FORECAST | TBATS | R | 
| 12 | TSLM_REGRESSION | TSLM (Time Series Linear Model) Regression | R | 
| 13 | VECTOR_REGRESSION | Vector Autoregression (VAR) | R | 
| 14 | SARIMA | Seasonal AutoRegressive Integrated Moving Average | Python |